November 17, 2022
For three years running, ACM has awarded not only its long-standing Gordon Bell Prize (read more about this year’s winner here!) but also its Gordon Bell Spec Read more…
November 17, 2022
Large language models (LLMs) have taken the tech world by storm over the past couple of years, dominating headlines with their ability to generate convincing hu Read more…
November 18, 2021
For the second (and, hopefully, final) year in a row, SC21 included a second major research award alongside the ACM 2021 Gordon Bell Prize: the Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research. Last year, the first iteration of this award went to simulations of the SARS-CoV-2 spike protein; this year, the prize went... Read more…
March 11, 2021
Four months ago, Rommie Amaro and her colleagues were accepting the first-ever Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research. Read more…
November 19, 2020
2020 has proven a harrowing year – but it has produced remarkable heroes. To that end, this year, the Association for Computing Machinery (ACM) introduced the Read more…
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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