AMD Delivers AMD EPYC and AMD Radeon Instinct Platforms at SC17

At SC17, AMD and its ecosystem partners announce immediate availability of a suite of new, high-performance systems powered by AMD EPYC CPUs and AMD Radeon Instinct GPUs. AMD combines this portfolio with software, featuring the new ROCm 1.7 open platform with updated development tools and libraries, enabling complete AMD EPYC-based PetaFLOPS systems.

By comprehensively supporting both heterogeneous supercomputing systems and memory-bound, CPU driven, high performance platforms with EPYC, AMD addresses the needs of multiple workloads. Target workloads for AMD solutions include machine learning, weather modeling, computational fluid dynamics, simulation and crash analysis in aviation and automotive manufacturing, and oil and gas exploration.

A highlight for AMD at SC17 is the Inventec P47 system that combines the performance of a single EPYC 7000 series CPU with four Radeon Instinct MI25 GPUs, each delivering up to 12.3 TFLOPS of single precision performance in a highly scalable platform. For large to hyperscale deployments, AMAX has developed the [SMART]Rack P47, an all-inclusive high-performance rackscale appliance featuring 20x P47 platforms to provide up to a PetaFLOPS of single precision compute performance and more than 10 terabytes of DDR4 memory per rack. The [SMART]Rack P47 also features HPC-optimized [SMART]DC DCiM software to remotely monitor, manage and orchestrate GPU-based deployments where real-time temperature, power and system health are important, as well as AMD’s ROCm software platform for ease of implementation for deep learning, inference and training workloads.

AMD EPYC and AMD Radeon Instinct performance is fully supported by the new ROCm 1.7 release. ROCm 1.7 delivers math libraries and software development support using modern programming languages to unlock the power of GPU acceleration and other accelerators like FPGAs. The ROCm 1.7 release includes multi-GPU support for the latest Radeon GPU hardware, as well as support for TensorFlow and Caffe in the MIOpen libraries.

For more info, visit AMD.

Sources: Press materials received from the company.