Optimizing Codes for Heterogeneous HPC Clusters Using OpenACC

July 3, 2017

Looking at the Top500 and Green500 ranks, one clearly realizes that most HPC systems are heterogeneous architecture using COTS (Commercial Off-The-Shelf) hardware, combining traditional multi-core CPUs with massively parallel accelerators, such as GPUs and MICs. With processor frequencies now hitting a solid wall, the only truly open avenue for riding today the Moore’s law is increasing hardware parallelism in several different ways: more computing nodes, more processors in each node, more cores within each processor, and longer vector instructions in each core. Read more…

Code Modernization: Bringing Codes Into the Parallel Age

June 8, 2017

The ways that advanced computing performance depends on more – much more – than the processor take many forms. Regardless of Moore’s Law validity, it’s Read more…

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn't made the task of parallel progr Read more…

MIT’s Multicore Swarm Architecture Advances Ordered Parallelism

July 21, 2016

A relatively new architecture explicitly designed for parallelism – Swarm – based on work at MIT has shown promise for substantially speeding up classes of Read more…

James Reinders: Parallelism Has Crossed a Threshold

February 4, 2016

Is the parallel everything era here? What happens when you can assume parallel cores? In the second half of our in-depth interview, Intel's James Reinders discu Read more…

A Conversation with James Reinders

January 21, 2016

As Chief Evangelist of Intel Software Products, James Reinders spends most of his working hours thinking about and promoting parallel programming. He’s ess Read more…

Intel Haswell-EX Server Sets STAC-A2 Performance Record

September 2, 2015

Intel has reasserted its prominence on a subset of financial benchmarks designed to evaluate platforms for the pricing and market risk analytics. More powerful Read more…

COSMOS Team Achieves 100x Speedup on Cosmology Code

August 24, 2015

One of the most popular sessions at the Intel Developer Forum last week in San Francisco, and certainly one of the most exciting from an HPC perspective, broug Read more…

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Whitepaper

Porting CUDA Applications to Run on AMD GPUs

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.

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Sponsored by AMD

Whitepaper

QCT HPC BeeGFS Storage: A Performance Environment for I/O Intensive Workloads

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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Sponsored by QCT

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