new-sat 2 x Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 b: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 c: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 d: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 e: Processor: Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 f: Processor: Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 g: Processor: Intel Xeon Max 9468 @ 3.50GHz (48 Cores / 96 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 h: Processor: Intel Xeon Max 9468 @ 3.50GHz (48 Cores / 96 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 i: Processor: Intel Xeon Max 9468 @ 3.50GHz (48 Cores / 96 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 j: Processor: 2 x Intel Xeon Max 9468 @ 3.50GHz (96 Cores / 192 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 k: Processor: 2 x Intel Xeon Max 9468 @ 3.50GHz (96 Cores / 192 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 l: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 m: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 n: Processor: 2 x Intel Xeon Platinum 8490H @ 3.50GHz (120 Cores / 240 Threads), Motherboard: Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS), Chipset: Intel Device 1bce, Memory: 1008GB, Disk: 3201GB Micron_7450_MTFDKCC3T2TFS, Graphics: ASPEED, Network: 2 x Intel X710 for 10GBASE-T OS: Ubuntu 23.10, Kernel: 6.6.0-rc5-phx-patched (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200 CloverLeaf 1.3 Input: clover_bm16 Seconds < Lower Is Better a . 224.98 |======== b . 214.08 |======== c . 218.67 |======== d . 303.86 |=========== e . 323.53 |============ f . 323.38 |============ g . 183.71 |======= h . 182.63 |======= j . 1584.37 |========================================================== k . 1812.17 |================================================================== n . 222.01 |======== DuckDB 0.9.1 Benchmark: IMDB Seconds < Lower Is Better a . 259.42 |=================================================================== d . 259.28 |=================================================================== DuckDB 0.9.1 Benchmark: TPC-H Parquet Seconds < Lower Is Better a . 178.04 |=================================================================== d . 178.83 |=================================================================== C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 256MB MB/s > Higher Is Better l . 5409.4 |=================================================================== m . 5333.4 |================================================================== n . 5324.3 |================================================================== C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 256MB MB/s > Higher Is Better l . 5615.4 |=================================================================== m . 5389.3 |================================================================ n . 5455.4 |================================================================= C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 256MB MB/s > Higher Is Better l . 5519.3 |================================================================== m . 5580.3 |=================================================================== n . 5520.6 |================================================================== QMCPACK 3.17.1 Input: O_ae_pyscf_UHF Total Execution Time - Seconds < Lower Is Better l . 214.65 |=================================================================== m . 207.84 |================================================================= n . 208.62 |================================================================= Timed Gem5 Compilation 23.0.1 Time To Compile Seconds < Lower Is Better e . 197.55 |============================================================= g . 206.08 |================================================================ h . 216.88 |=================================================================== j . 195.49 |============================================================ k . 197.95 |============================================================= l . 168.58 |==================================================== m . 162.39 |================================================== n . 165.81 |=================================================== C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 128MB MB/s > Higher Is Better l . 8089.4 |=================================================================== m . 8059.2 |=================================================================== n . 7960.2 |================================================================== C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 128MB MB/s > Higher Is Better l . 8697.6 |================================================================== m . 8864.5 |=================================================================== n . 8289.6 |=============================================================== C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 128MB MB/s > Higher Is Better l . 8707.4 |=================================================================== m . 8640.0 |================================================================== n . 8564.3 |================================================================== QMCPACK 3.17.1 Input: FeCO6_b3lyp_gms Total Execution Time - Seconds < Lower Is Better l . 128.73 |=================================================================== m . 129.20 |=================================================================== n . 129.23 |=================================================================== C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 64MB MB/s > Higher Is Better l . 11321.9 |================================================================== m . 11315.0 |================================================================== n . 11238.1 |================================================================== C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 64MB MB/s > Higher Is Better l . 11927.7 |================================================================== m . 11905.5 |================================================================== n . 11839.7 |================================================================== C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 64MB MB/s > Higher Is Better l . 12239.3 |================================================================== m . 12161.8 |================================================================== n . 12008.0 |================================================================= OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 8459 |============================== b . 8429 |============================== d . 8493 |============================== e . 15787 |========================================================= g . 18877 |==================================================================== h . 18945 |==================================================================== j . 13319 |================================================ k . 13049 |=============================================== n . 8428 |============================== C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 8MB MB/s > Higher Is Better l . 12794.5 |================================================================== m . 12855.3 |================================================================== n . 12742.3 |================================================================= OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 7192 |============================== b . 7193 |============================== d . 7245 |=============================== e . 13393 |======================================================== g . 16151 |==================================================================== h . 16114 |==================================================================== j . 11801 |================================================== k . 11652 |================================================= n . 7194 |============================== OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 4239 |=============================== b . 4213 |=============================== d . 4258 |=============================== e . 7892 |========================================================= g . 9424 |===================================================================== h . 9487 |===================================================================== j . 6496 |=============================================== k . 7011 |=================================================== n . 4206 |=============================== QMCPACK 3.17.1 Input: Li2_STO_ae Total Execution Time - Seconds < Lower Is Better l . 99.82 |==================================================================== m . 98.18 |=================================================================== n . 99.26 |==================================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 7076 |============================== b . 7113 |============================== d . 7142 |============================== e . 13272 |========================================================= f . 13231 |======================================================== g . 15955 |==================================================================== h . 15942 |==================================================================== j . 10852 |============================================== k . 10581 |============================================= n . 7076 |============================== OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 3539 |=============================== b . 3542 |=============================== d . 3558 |=============================== e . 6633 |========================================================== f . 6628 |========================================================== g . 7939 |===================================================================== h . 7952 |===================================================================== j . 5349 |============================================== k . 5771 |================================================== n . 3545 |=============================== OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 3620 |=============================== b . 3594 |=============================== d . 3636 |=============================== e . 6711 |========================================================== f . 6711 |========================================================== g . 8009 |===================================================================== h . 8010 |===================================================================== j . 5659 |================================================= k . 5812 |================================================== n . 3605 |=============================== QMCPACK 3.17.1 Input: LiH_ae_MSD Total Execution Time - Seconds < Lower Is Better l . 94.27 |==================================================================== m . 94.02 |==================================================================== n . 94.30 |==================================================================== OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 14223 |========================== b . 14248 |========================== d . 14338 |=========================== e . 31373 |========================================================== f . 31194 |========================================================== g . 36770 |==================================================================== h . 36787 |==================================================================== j . 22407 |========================================= k . 22062 |========================================= n . 14289 |========================== C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 8MB MB/s > Higher Is Better l . 14338.2 |================================================================== m . 14241.2 |================================================================== n . 14082.4 |================================================================= C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 32MB MB/s > Higher Is Better l . 14712.6 |================================================================== m . 14746.7 |================================================================== n . 14569.9 |================================================================= C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 8MB MB/s > Higher Is Better l . 14873.2 |================================================================== m . 14846.5 |================================================================== n . 14815.4 |================================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 14067 |========================== b . 13991 |========================== d . 14042 |========================== e . 30876 |========================================================= f . 30951 |========================================================= g . 36833 |==================================================================== h . 36575 |==================================================================== j . 31587 |========================================================== k . 21000 |======================================= n . 14017 |========================== Cpuminer-Opt 23.5 Algorithm: Garlicoin kH/s > Higher Is Better a . 3725.51 |========= b . 3727.55 |========= d . 4200.71 |=========== e . 11540.00 |============================= g . 2256.38 |====== h . 2332.32 |====== j . 20460.00 |=================================================== k . 20550.00 |=================================================== n . 26000.00 |================================================================= C-Blosc 2.11 Test: blosclz noshuffle - Buffer Size: 16MB MB/s > Higher Is Better l . 15231.9 |================================================================== m . 15269.2 |================================================================== n . 15041.6 |================================================================= OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 230 |================================ b . 230 |================================ d . 231 |================================ e . 421 |========================================================== f . 422 |========================================================== g . 505 |====================================================================== h . 505 |====================================================================== j . 361 |================================================== k . 370 |=================================================== n . 230 |================================ OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 269 |================================ b . 268 |================================ d . 270 |================================ e . 496 |========================================================== f . 497 |========================================================== g . 595 |====================================================================== h . 595 |====================================================================== j . 420 |================================================= k . 450 |===================================================== n . 268 |================================ C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 32MB MB/s > Higher Is Better l . 15811.9 |================================================================== m . 15827.9 |================================================================== n . 15691.0 |================================================================= OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 225 |================================ b . 226 |================================ d . 227 |================================ e . 416 |========================================================== f . 416 |========================================================== g . 500 |====================================================================== h . 500 |====================================================================== j . 356 |================================================== k . 344 |================================================ n . 225 |================================ C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 32MB MB/s > Higher Is Better l . 16111.4 |================================================================== m . 16050.9 |================================================================== n . 15827.9 |================================================================= OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 1066 |=============================== b . 1064 |=============================== d . 1064 |=============================== e . 1962 |========================================================== f . 1962 |========================================================== g . 2352 |===================================================================== h . 2345 |===================================================================== j . 1691 |================================================== k . 1672 |================================================= n . 1057 |=============================== C-Blosc 2.11 Test: blosclz shuffle - Buffer Size: 16MB MB/s > Higher Is Better l . 16680.2 |================================================================== m . 16762.6 |================================================================== n . 16392.9 |================================================================= C-Blosc 2.11 Test: blosclz bitshuffle - Buffer Size: 16MB MB/s > Higher Is Better l . 16895.0 |================================================================== m . 16810.4 |================================================================== n . 16633.4 |================================================================= OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 907 |=============================== b . 908 |=============================== d . 910 |================================ e . 1663 |========================================================== f . 1661 |========================================================== g . 1990 |===================================================================== h . 1989 |===================================================================== j . 1535 |===================================================== k . 1381 |================================================ n . 903 |=============================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 889 |=============================== b . 889 |=============================== d . 894 |=============================== e . 1644 |========================================================= f . 1647 |========================================================= g . 1984 |===================================================================== h . 1975 |===================================================================== j . 1366 |================================================ k . 1361 |=============================================== n . 889 |=============================== OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 38573 |================================= b . 38554 |================================= d . 39029 |================================= e . 67291 |========================================================= f . 67337 |========================================================= g . 80104 |==================================================================== h . 79992 |==================================================================== j . 60905 |==================================================== k . 59689 |=================================================== n . 38979 |================================= OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 34608 |================================== b . 33567 |================================= d . 33817 |================================== e . 58032 |========================================================== f . 58436 |========================================================== g . 68506 |==================================================================== h . 68593 |==================================================================== j . 51940 |=================================================== k . 52535 |==================================================== n . 33789 |================================= OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 16770 |=========================== b . 16786 |=========================== d . 16765 |=========================== e . 36028 |========================================================== f . 36109 |========================================================== g . 42592 |==================================================================== h . 42412 |==================================================================== j . 30736 |================================================= k . 34459 |======================================================= n . 16672 |=========================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 33358 |================================= b . 33490 |================================= d . 33652 |================================= e . 57130 |========================================================= f . 57572 |========================================================= g . 68562 |==================================================================== h . 68355 |==================================================================== j . 51593 |=================================================== k . 48393 |================================================ n . 33085 |================================= Cpuminer-Opt 23.5 Algorithm: Ringcoin kH/s > Higher Is Better a . 5799.03 |======================== b . 5933.75 |======================== d . 5770.26 |======================== e . 5867.89 |======================== g . 5205.00 |===================== h . 5300.21 |====================== j . 15560.00 |================================================================ k . 15770.00 |================================================================= n . 7748.29 |================================ OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better e . 360.89 |=================================================================== g . 244.29 |============================================= h . 244.11 |============================================= j . 258.62 |================================================ k . 261.89 |================================================= l . 288.36 |====================================================== m . 288.29 |====================================================== n . 289.07 |====================================================== OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better e . 165.82 |=========================== g . 196.21 |================================ h . 196.28 |================================ j . 370.50 |============================================================ k . 365.91 |=========================================================== l . 415.38 |=================================================================== m . 415.53 |=================================================================== n . 414.39 |=================================================================== OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU ms < Lower Is Better e . 16.72 |==================================================================== g . 13.00 |===================================================== h . 13.03 |===================================================== j . 13.68 |======================================================== k . 13.59 |======================================================= l . 15.66 |================================================================ m . 15.63 |================================================================ n . 15.59 |=============================================================== OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU FPS > Higher Is Better e . 3566.26 |=============================== g . 3685.78 |================================ h . 3678.97 |================================ j . 6992.06 |============================================================ k . 7049.72 |============================================================= l . 7617.42 |================================================================== m . 7626.39 |================================================================== n . 7650.29 |================================================================== OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU ms < Lower Is Better e . 385.45 |=================================================================== g . 114.95 |==================== h . 115.13 |==================== j . 124.17 |====================== k . 125.39 |====================== l . 137.34 |======================== m . 137.23 |======================== n . 137.61 |======================== OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU FPS > Higher Is Better e . 77.69 |======================== g . 104.31 |================================ h . 104.12 |================================ j . 193.11 |=========================================================== k . 191.20 |=========================================================== l . 218.22 |=================================================================== m . 218.39 |=================================================================== n . 217.79 |=================================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU ms < Lower Is Better e . 54.30 |=========================================================== g . 51.91 |======================================================== h . 51.84 |======================================================== j . 56.00 |============================================================= k . 56.11 |============================================================= l . 62.61 |==================================================================== m . 62.56 |==================================================================== n . 62.67 |==================================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU FPS > Higher Is Better e . 1101.87 |====================================== g . 923.91 |================================ h . 925.43 |================================ j . 1712.71 |=========================================================== k . 1709.38 |=========================================================== l . 1914.91 |================================================================== m . 1915.98 |================================================================== n . 1912.82 |================================================================== OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU ms < Lower Is Better e . 103.21 |=================================================================== g . 35.35 |======================= h . 35.35 |======================= j . 37.93 |========================= k . 38.26 |========================= l . 47.07 |=============================== m . 46.98 |============================== n . 46.94 |============================== OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU FPS > Higher Is Better e . 290.36 |============================== g . 339.17 |==================================== h . 339.22 |==================================== j . 632.07 |================================================================== k . 626.67 |================================================================== l . 636.90 |=================================================================== m . 638.13 |=================================================================== n . 638.56 |=================================================================== OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU ms < Lower Is Better e . 103.01 |=================================================================== g . 35.39 |======================= h . 35.41 |======================= j . 37.98 |========================= k . 38.23 |========================= l . 47.10 |=============================== m . 46.87 |============================== n . 47.14 |=============================== OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU FPS > Higher Is Better e . 290.88 |============================== g . 338.84 |=================================== h . 338.61 |=================================== j . 631.31 |================================================================== k . 627.12 |================================================================== l . 636.48 |=================================================================== m . 639.58 |=================================================================== n . 635.92 |=================================================================== OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU ms < Lower Is Better e . 64.66 |==================================================================== g . 27.53 |============================= h . 27.75 |============================= j . 29.63 |=============================== k . 29.75 |=============================== l . 40.61 |=========================================== m . 40.04 |========================================== n . 40.90 |=========================================== OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU FPS > Higher Is Better e . 462.66 |====================================== g . 433.90 |==================================== h . 430.23 |==================================== j . 806.26 |=================================================================== k . 803.87 |=================================================================== l . 733.98 |============================================================= m . 744.86 |============================================================== n . 729.58 |============================================================= OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU ms < Lower Is Better e . 18.43 |============================================================= g . 14.44 |================================================ h . 14.46 |================================================ j . 15.33 |=================================================== k . 15.43 |=================================================== l . 20.51 |==================================================================== m . 20.53 |==================================================================== n . 20.62 |==================================================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU FPS > Higher Is Better e . 3221.62 |================================== g . 3319.81 |=================================== h . 3314.00 |=================================== j . 6234.26 |================================================================== k . 6196.74 |================================================================== l . 5831.93 |============================================================== m . 5825.24 |============================================================== n . 5799.67 |============================================================= OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU ms < Lower Is Better e . 6.28 |===================================================================== g . 5.40 |=========================================================== h . 5.41 |=========================================================== j . 5.65 |============================================================== k . 5.65 |============================================================== l . 5.68 |============================================================== m . 5.68 |============================================================== n . 5.69 |=============================================================== OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU FPS > Higher Is Better e . 9344.43 |============================= g . 8871.46 |=========================== h . 8855.95 |=========================== j . 16935.65 |==================================================== k . 16935.03 |==================================================== l . 21075.26 |================================================================= m . 21071.09 |================================================================= n . 21033.04 |================================================================= OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU ms < Lower Is Better e . 9.66 |===================================================================== g . 7.28 |==================================================== h . 7.30 |==================================================== j . 7.62 |====================================================== k . 7.64 |======================================================= l . 8.02 |========================================================= m . 8.02 |========================================================= n . 8.05 |========================================================== OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU FPS > Higher Is Better e . 6106.91 |=========================== g . 6581.71 |============================= h . 6566.24 |============================= j . 12561.59 |======================================================= k . 12534.63 |======================================================= l . 14938.83 |================================================================= m . 14932.70 |================================================================= n . 14888.49 |================================================================= OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU ms < Lower Is Better e . 0.48 |===================================================================== g . 0.30 |=========================================== h . 0.30 |=========================================== j . 0.31 |============================================= k . 0.31 |============================================= l . 0.29 |========================================== m . 0.29 |========================================== n . 0.29 |========================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU FPS > Higher Is Better e . 106187.70 |============================================= g . 131083.06 |======================================================= h . 131445.26 |======================================================= j . 114581.51 |================================================ k . 119756.16 |=================================================== l . 151691.73 |================================================================ m . 150804.01 |================================================================ n . 146682.31 |============================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better e . 0.61 |===================================================================== g . 0.51 |========================================================== h . 0.52 |=========================================================== j . 0.41 |============================================== k . 0.41 |============================================== l . 0.37 |========================================== m . 0.38 |=========================================== n . 0.38 |=========================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better e . 86847.05 |======================================= g . 90384.31 |======================================== h . 88444.43 |======================================= j . 115992.72 |=================================================== k . 103901.05 |============================================== l . 144299.06 |================================================================ m . 142293.67 |=============================================================== n . 142499.69 |=============================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU ms < Lower Is Better e . 39.86 |==================================================================== g . 17.55 |============================== h . 17.58 |============================== j . 18.68 |================================ k . 18.82 |================================ l . 19.58 |================================= m . 19.57 |================================= n . 19.58 |================================= OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU FPS > Higher Is Better e . 751.14 |================================ g . 682.77 |============================= h . 681.90 |============================= j . 1283.22 |======================================================= k . 1273.73 |======================================================= l . 1530.63 |================================================================== m . 1531.37 |================================================================== n . 1530.84 |================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU ms < Lower Is Better e . 48.77 |==================================================================== g . 39.95 |======================================================== h . 40.22 |======================================================== j . 40.39 |======================================================== k . 40.36 |======================================================== l . 39.91 |======================================================== m . 39.91 |======================================================== n . 40.09 |======================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU FPS > Higher Is Better e . 1224.11 |=========================== g . 1200.82 |========================== h . 1192.76 |========================== j . 2375.20 |==================================================== k . 2377.19 |==================================================== l . 3004.85 |================================================================== m . 3004.85 |================================================================== n . 2991.51 |================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU ms < Lower Is Better e . 38.54 |==================================================================== g . 24.23 |=========================================== h . 24.12 |=========================================== j . 24.52 |=========================================== k . 24.48 |=========================================== l . 27.30 |================================================ m . 27.35 |================================================ n . 27.04 |================================================ OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU FPS > Higher Is Better e . 1545.36 |======================= g . 1979.56 |============================= h . 1988.30 |============================== j . 3910.94 |========================================================== k . 3918.19 |========================================================== l . 4387.28 |================================================================= m . 4379.43 |================================================================= n . 4433.69 |================================================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU ms < Lower Is Better e . 3.51 |===================================================================== g . 2.47 |================================================= h . 2.49 |================================================= j . 2.68 |===================================================== k . 2.74 |====================================================== l . 2.52 |================================================== m . 2.51 |================================================= n . 2.52 |================================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU FPS > Higher Is Better e . 16489.33 |======================= g . 19358.98 |=========================== h . 19208.93 |========================== j . 35303.47 |================================================ k . 34620.99 |=============================================== l . 47357.41 |================================================================= m . 47468.22 |================================================================= n . 47369.39 |================================================================= OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU ms < Lower Is Better e . 6.44 |===================================================================== g . 4.36 |=============================================== h . 4.06 |============================================ j . 4.38 |=============================================== k . 4.42 |=============================================== l . 4.35 |=============================================== m . 4.35 |=============================================== n . 4.35 |=============================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU FPS > Higher Is Better e . 9078.33 |====================== g . 10978.58 |========================== h . 11783.36 |============================ j . 21815.71 |==================================================== k . 21635.47 |==================================================== l . 27232.91 |================================================================= m . 27109.50 |================================================================= n . 27112.85 |================================================================= OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better e . 15.86 |==================================================================== g . 6.35 |=========================== h . 6.34 |=========================== j . 6.87 |============================= k . 6.90 |============================== l . 7.69 |================================= m . 7.69 |================================= n . 7.69 |================================= OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better e . 1878.87 |================================ g . 1884.46 |================================ h . 1889.02 |================================ j . 3484.18 |=========================================================== k . 3465.57 |=========================================================== l . 3893.77 |================================================================== m . 3895.49 |================================================================== n . 3895.01 |================================================================== CloverLeaf 1.3 Input: clover_bm64_short Seconds < Lower Is Better a . 24.34 |============== b . 24.97 |============== c . 24.12 |============== d . 32.19 |================== e . 38.96 |====================== f . 38.94 |====================== g . 20.86 |============ h . 20.99 |============ j . 117.20 |=================================================================== k . 73.01 |========================================== n . 24.90 |============== Cpuminer-Opt 23.5 Algorithm: Skeincoin kH/s > Higher Is Better a . 133860 |=================================================================== b . 133600 |=================================================================== d . 134140 |=================================================================== e . 67000 |================================= g . 50420 |========================= h . 48010 |======================== j . 95670 |================================================ k . 95990 |================================================ n . 133840 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Blake-2 S kH/s > Higher Is Better a . 535240 |=================================================================== b . 535430 |=================================================================== d . 533880 |=================================================================== e . 267760 |================================== g . 191940 |======================== h . 191940 |======================== j . 382680 |================================================ k . 382610 |================================================ n . 534840 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Magi kH/s > Higher Is Better a . 2683.56 |================================================================== b . 2681.44 |================================================================== d . 2672.68 |================================================================= e . 1370.86 |================================== g . 968.45 |======================== h . 986.33 |======================== j . 1946.40 |================================================ k . 1946.34 |================================================ n . 2694.61 |================================================================== Cpuminer-Opt 23.5 Algorithm: LBC, LBRY Credits kH/s > Higher Is Better a . 58960 |=================================================================== b . 59690 |==================================================================== d . 58620 |=================================================================== e . 29550 |================================== g . 21190 |======================== h . 21180 |======================== j . 42230 |================================================ k . 42230 |================================================ n . 59060 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Quad SHA-256, Pyrite kH/s > Higher Is Better a . 267960 |================================================================== b . 269860 |=================================================================== d . 267450 |================================================================== e . 136700 |================================== g . 97890 |======================== h . 97960 |======================== j . 195710 |================================================ k . 196100 |================================================ n . 271570 |=================================================================== Cpuminer-Opt 23.5 Algorithm: scrypt kH/s > Higher Is Better a . 1220.91 |================================================================== b . 1194.30 |================================================================= d . 1189.10 |================================================================ e . 618.59 |================================= g . 472.76 |========================== h . 456.46 |========================= j . 939.58 |=================================================== k . 900.68 |================================================= n . 1201.63 |================================================================= Cpuminer-Opt 23.5 Algorithm: Deepcoin kH/s > Higher Is Better a . 32300 |==================================================================== b . 32320 |==================================================================== d . 32317 |==================================================================== e . 16340 |================================== g . 11730 |========================= h . 12140 |========================= j . 23390 |================================================= k . 23850 |================================================== n . 32400 |==================================================================== Cpuminer-Opt 23.5 Algorithm: Triple SHA-256, Onecoin kH/s > Higher Is Better a . 384930 |=================================================================== b . 384820 |=================================================================== d . 384423 |=================================================================== e . 194980 |================================== g . 139540 |======================== h . 140170 |======================== j . 278140 |================================================ k . 278150 |================================================ n . 385290 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Myriad-Groestl kH/s > Higher Is Better a . 47950 |==================================================================== b . 46280 |================================================================== d . 47623 |==================================================================== e . 25310 |==================================== g . 17860 |========================= h . 18010 |========================== j . 35700 |=================================================== k . 35610 |=================================================== n . 46430 |================================================================== QMCPACK 3.17.1 Input: simple-H2O Total Execution Time - Seconds < Lower Is Better l . 29.29 |==================================================================== m . 29.19 |==================================================================== n . 29.15 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.10 |==================================================================== b . 80.47 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.82 |==================================================================== b . 81.97 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.72 |==================================================================== b . 82.77 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 82.66 |==================================================================== b . 82.83 |==================================================================== CloverLeaf 1.3 Input: clover_bm Seconds < Lower Is Better a . 14.03 |============ b . 13.69 |============ c . 14.05 |============ d . 19.28 |================= e . 8.74 |======== f . 8.68 |======= g . 10.00 |========= h . 9.87 |========= i . 9.94 |========= j . 78.70 |==================================================================== k . 63.32 |======================================================= n . 14.07 |============ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 138.03 |=================================================================== b . 136.46 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 137.37 |=================================================================== b . 137.38 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 154.94 |=================================================================== b . 155.04 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 1024 GFLOP/s > Higher Is Better a . 154.89 |=================================================================== b . 154.81 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 151.72 |=================================================================== b . 152.47 |=================================================================== c . 152.04 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 153.32 |=================================================================== b . 153.99 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 152.25 |=================================================================== b . 153.36 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 152.49 |=================================================================== b . 152.92 |=================================================================== QMCPACK 3.17.1 Input: H4_ae Total Execution Time - Seconds < Lower Is Better l . 12.52 |=================================================================== m . 12.68 |==================================================================== n . 12.70 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 262.19 |=================================================================== b . 262.09 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 261.58 |=================================================================== b . 262.00 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 1024 GFLOP/s > Higher Is Better a . 298.19 |=================================================================== b . 297.89 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 1024 GFLOP/s > Higher Is Better a . 299.64 |=================================================================== b . 297.94 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 67.01 |==================================================================== b . 66.19 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 69.69 |==================================================================== b . 65.41 |================================================================ c . 65.12 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 72.03 |==================================================================== b . 71.31 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 71.74 |==================================================================== b . 71.46 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 123.79 |=================================================================== b . 122.95 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 124.49 |=================================================================== b . 123.11 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 119.58 |============================================================== b . 129.55 |=================================================================== c . 118.43 |============================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 128.23 |================================================================== b . 129.79 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 136.09 |=================================================================== b . 133.27 |================================================================== c . 130.46 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 133.76 |=================================================================== b . 131.44 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 135.65 |=================================================================== b . 132.37 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 134.08 |=================================================================== b . 133.67 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 242.76 |================================================================== b . 245.52 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 246.42 |=================================================================== b . 238.18 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 244.61 |=================================================================== b . 241.84 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 242.80 |=================================================================== b . 238.31 |================================================================== c . 236.92 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 67.45 |==================================================================== b . 63.59 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 64.85 |==================================================================== b . 63.68 |=================================================================== c . 62.71 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 67.43 |==================================================================== b . 65.55 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 65.75 |=================================================================== b . 67.00 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 71.48 |==================================================== b . 66.64 |================================================= c . 92.64 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 127.35 |================================================================= b . 131.69 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 172.19 |=================================================================== b . 157.03 |============================================================= c . 159.46 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 159.22 |============================================================== b . 173.45 |=================================================================== c . 160.51 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 162.02 |=================================================================== b . 158.12 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 166.06 |=================================================================== b . 158.01 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 149.78 |=================================================================== b . 146.84 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 156.74 |=================================================================== b . 157.55 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 89.76 |==================================================== b . 41.56 |======================== c . 115.40 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 130.15 |=============================================================== b . 138.93 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 360.02 |=================================================================== b . 323.21 |============================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 323.08 |============================================================== b . 348.23 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 345.60 |=================================================================== b . 331.45 |================================================================ c . 341.13 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 175.04 |=================================================================== b . 176.18 |=================================================================== c . 175.27 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 87.91 |================================================================== b . 90.23 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 71.96 |==================================================================== b . 38.50 |==================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 29.78 |====================== b . 92.73 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 322.72 |================================================================== b . 327.72 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 123.36 |=================================================================== b . 123.26 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 164.82 |=================================================================== b . 158.42 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 161.82 |=================================================================== b . 161.36 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 165.32 |=============================================================== b . 175.74 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 125.36 |=================================================================== b . 126.18 |=================================================================== c . 108.63 |========================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 143.40 |=================================================================== b . 132.64 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 115.20 |============================================================= b . 125.70 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 140.10 |================================================================= b . 145.30 |=================================================================== c . 144.14 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 89.02 |=================================================================== b . 90.01 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 120.20 |================================================================= b . 124.55 |===================================================================