April 26, 2022
In the third of a series of guest posts on heterogeneous computing, James Reinders shares experiences surrounding the creation of ASCI Red and ties that system' Read more…
October 9, 2015
The High Performance Computing Center Stuttgart (HLRS), member of the Gauss Centre for Supercomputing, today reported completion of the second upgrade of its su Read more…
March 26, 2015
The Indian government has approved a seven-year supercomputing program worth $730 million (Rs. 4,500-crore) intended to restore the nation's status as a world- Read more…
May 28, 2013
When so many folks from the HPC community come at us with credible details about something as important as the next top system on the planet, it's hard to ignore. To quiet things down (and hopefully bring forth more information) we've published the consistent details about what we know from (very) credible sources.about this year's upcoming Top500 announcement. While unconfimed, we have.... 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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