The Frontier supercomputer – still fresh off its chart-topping 1.1 Linpack exaflops run and maintaining its number-one spot on the Top500 list – was still very much in the spotlight at SC22 i …
The race to ever-better flops-per-watt and power usage effectiveness (PUE) has, historically, dominated the conversation over sustainability in HPC – but at SC22, held last month in Dallas, som …
In this monthly feature, we’ll keep you up-to-date on the latest career developments for individuals in the high-performance computing community. Whether it’s a promotion, new company hire, o …
Part scorecard, part grand vision, IBM’s annual Quantum Summit held last month is a fascinating snapshot of IBM’s progress, evolving technology roadmap, and issues facing the quantum landscap …
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Giving developers the ability to write code once and use it on different platforms is important. Organizations are increasingly moving to open source and open standard solutions which can aid in code portability. AMD developed a porting solution that allows developers to port proprietary NVIDIA® CUDA® code to run on AMD graphic processing units (GPUs).
This paper describes the AMD ROCm™ open software platform which provides porting tools to convert NVIDIA CUDA code to AMD native open-source Heterogeneous Computing Interface for Portability (HIP) that can run on AMD Instinct™ accelerator hardware. The AMD solution addresses performance and portability needs of artificial intelligence (AI), machine learning (ML) and high performance computing (HPC) for application developers. Using the AMD ROCm platform, developers can port their GPU applications to run on AMD Instinct accelerators with very minimal changes to be able to run their code in both NVIDIA and AMD environments.
A workload-driven system capable of running HPC/AI workloads is more important than ever. Organizations face many challenges when building a system capable of running HPC and AI workloads. There are also many complexities in system design and integration. Building a workload driven solution requires expertise and domain knowledge that organizational staff may not possess.
This paper describes how Quanta Cloud Technology (QCT), a long-time Intel® partner, developed the Taiwania 2 and Taiwania 3 supercomputers to meet the research needs of the Taiwan’s academic, industrial, and enterprise users. The Taiwan National Center for High-Performance Computing (NCHC) selected QCT for their expertise in building HPC/AI supercomputers and providing worldwide end-to-end support for solutions from system design, through integration, benchmarking and installation for end users and system integrators to ensure customer success.
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