Versatile training and inference accelerator for machine intelligence and deep learning.
Based on the “Polaris” GRAPHICS ARCHITECTURE built to tackle training and inference workloads
36 COMPUTE UNITS available to run many smaller batches of data simultaneously against trained deep learning neural networks
Up to 5.7 TFLOPS of peak FP32 and FP16 compute performance to speed up compute intensive machine intelligence
38 GFLOPS/watt peak FP16/FP32 performance. Offering a great low-cost, highly-efficient server solution for inference and edge-training
16GB of GDDR5 MEMORY, up to 224GB/s memory bandwidth
Passively cooled, 150W TDP board power – single slot board designed to fit in most standard server designs
MxGPU for Virtualized Compute Workloads – drive greater utilization and capacity in the data center
ROCm Software Platform provides open source Hyperscale and HPC-class solutions
Inference and Edge Training for Deep Learning
ROCm software platform provides open source Hyperscale platform
Open source Linux® drivers, HCC compiler, tools and libraries for full control from the metal forward
Optimized MIOpen deep learning framework libraries
Large BAR support for mGPU peer to peer
MxGPU SR-IOV hardware virtualization for optimized system utilizations
Open industry standard support of multiple architectures and industry standard interconnect technologies
HPC General Purpose and Development
ROCm software platform provides open source HPC-class platform
Open source Linux® drivers, HCC compiler, tools and libraries for full control from the metal forward
MxGPU SR-IOV hardware virtualization for optimized system utilizations