May 3, 2022
Control of quantum computers has always required fast, precise coordination between a traditional computer and the quantum computer. Mostly, these are custom sy Read more…
January 15, 2021
Over the course of the last year, many detailed computational models of SARS-CoV-2 have been produced with the help of supercomputers, but those models have lar Read more…
March 27, 2018
The lithium ion battery, which essentially transformed portable electronics, has been a tough act to follow. Last week, researchers from Argonne National Labora Read more…
September 19, 2017
The National Science Foundation has awarded a second phase, $10 million grant to the Chameleon cloud computing testbed project led by University of Chicago with Read more…
May 5, 2016
Chameleon, the NSF-funded cloud testbed co-located at the University of Chicago and the Texas Advanced Computing Center, has been operating less than one year, 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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