Sign up for our newsletter and get the latest HPC news and analysis.
Send me information from insideHPC:


Allinea to Showcase V7.1 Performance Tools at ISC 2017

Today Allinea software, now part of ARM, announced plans to preview the latest update to its powerful tool suite for developing and optimizing high performance and scientific applications at ISC17 in Frankfurt. “Eliminating performance loss across systems and minimizing the communication overhead often make a critical difference in improving application run times in HPC. We believe that our extended cross-platform support will enable users to achieve unprecedented results by running their systems more efficiently on each of the major platforms and even across platforms,” said Mark O’Connor, director of product management, server and HPC tools, ARM.

Rock Stars of HPC: DK Panda

As our newest Rock Star of HPC, DK Panda sat down with us to discuss his passion for teaching High Performance Computing. “During the last several years, HPC systems have been going through rapid changes to incorporate accelerators. The main software challenges for such systems have been to provide efficient support for programming models with high performance and high productivity. For NVIDIA-GPU based systems, seven years back, my team introduced a novel `CUDA-aware MPI’ concept. This paradigm allows complete freedom to application developers for not using CUDA calls to perform data movement.”

Rock Stars of HPC: John Stone

This Rock Stars of HPC series is about the men and women who are changing the way the HPC community develops, deploys, and operates the supercomputers and social and economic impact of their discoveries. “As the lead developer of the VMD molecular visualization and analysis tool, John Stone’s code is used by more than 100,000 researchers around the world. He’s also a CUDA Fellow, helping to bring HPC to the masses with accelerated computing. In this way and many others, John Stone is certainly one of the Rock Stars of HPC.”

Register Now for the SDSC Summer Institute on HPC

“This year’s workshop continues SDSC’s strategy of bringing high-performance computing to what is known as the ‘long tail’ of science, i.e. providing resources to a larger and more diverse number of modest-sized computational research projects that represent, in aggregate, a tremendous amount of scientific research and discovery. SDSC has developed and hosted Summer Institute workshops for well over a decade.”

Introduction to GPUs in HPC

“This video is from the opening session of the “Introduction to Programming Pascal (P100) with CUDA 8″ workshop at CSCS in Lugano, Switzerland. The three-day course is intended to offer an introduction to Pascal computing using CUDA 8.”

CUDA Made Easy: An Introduction

“CUDA C++ is just one of the ways you can create massively parallel applications with CUDA. It lets you use the powerful C++ programming language to develop high performance algorithms accelerated by thousands of parallel threads running on GPUs. Many developers have accelerated their computation- and bandwidth-hungry applications this way, including the libraries and frameworks that underpin the ongoing revolution in artificial intelligence known as Deep Learning.”

Apply Now for Summer of HPC 2017 in Barcelona

“The PRACE Summer of HPC is an outreach and training program that offers summer placements at top High Performance Computing centers across Europe to late-stage undergraduates and early-stage postgraduate students. Up to twenty top applicants from across Europe will be selected to participate. Participants will spend two months working on projects related to PRACE technical or industrial work and produce a report and a visualization or video of their results.”

Allinea Adds CUDA 8 Support for GPU Developers

Today Allinea Software announces availability of its new software release, version 6.1, which offers full support for programming parallel code on the Pascal GPU architecture, CUDA 8 from Nvidia. “The addition of Allinea tools into the mix is an exciting one, enabling teams to accurately measure GPU utilization, employ smart optimization techniques and quickly develop new CUDA 8 code that is bug and bottleneck free,” said Mark O’Connor, VP of Product Management at Allinea.

ArrayFire v3.4 Parallel Computing Library Speeds Machine Learning

Today ArrayFire released the latest version of their ArrayFire open source library of parallel computing functions supporting CUDA, OpenCL, and CPU devices. ArrayFire v3.4 improves features and performance for applications in machine learning, computer vision, signal processing, statistics, finance, and more.

Tutorial: GPU Performance Nuggets

In this video from the 2016 Blue Waters Symposium, GPU Performance Nuggets – Carl Pearson and Simon Garcia De Gonzalo from the University of Illinois present: GPU Performance Nuggets. “In this talk, we introduce a pair of Nvidia performance tools available on Blue Waters. We discuss what the GPU memory hierarchy provides for your application. We then present a case study that explores if memory hierarchy optimization can go too far.”