tri
tri


tri: 

	Processor: AMD EPYC 7543P 32-Core (4 Cores / 8 Threads), Motherboard: Blade Shadow ShadowM v2.0 (1.1.3 BIOS), Chipset: Intel 82G33/G31/P35/P31 + ICH9, Memory: 1 x 16GB RAM-2400MT/s Blade 2MEVPUH6DW9W57-PYL, Disk: 215GB QEMU HDD, Graphics: Red Hat QXL paravirtual graphic card 20GB, Network: Red Hat Virtio device

	OS: Ubuntu 22.04, Kernel: 5.15.0-113-generic (x86_64), Display Server: X Server, Display Driver: NVIDIA, OpenCL: OpenCL 3.0 CUDA 12.4.131, Vulkan: 1.3.277, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 1280x800, System Layer: KVM


AI Benchmark Alpha 0.1.2
Device AI Score
Score > Higher Is Better
tri . 1530 |===================================================================


AI Benchmark Alpha 0.1.2
Device Training Score
Score > Higher Is Better
tri . 814 |====================================================================


AI Benchmark Alpha 0.1.2
Device Inference Score
Score > Higher Is Better
tri . 716 |====================================================================


TensorFlow 2.16.1
Device: GPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
tri . 3.40 |===================================================================


TensorFlow 2.16.1
Device: GPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
tri . 11.62 |==================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
images/sec > Higher Is Better
tri . 8.53 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
tri . 25.54 |==================================================================


TensorFlow 2.16.1
Device: GPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
tri . 14.44 |==================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
tri . 44.22 |==================================================================


TensorFlow 2.16.1
Device: GPU - Batch Size: 16 - Model: VGG-16
images/sec > Higher Is Better
tri . 1.14 |===================================================================


TensorFlow 2.16.1
Device: CPU - Batch Size: 16 - Model: VGG-16
images/sec > Higher Is Better
tri . 3.25 |===================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
tri . 3.88 |===================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
tri . 5.76 |===================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
tri . 14.81 |==================================================================