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


ArrayFire Releases v3.6 Parallel Libraries

Today ArrayFire announced the release of ArrayFire v3.6, the company’s open source library of parallel computing functions supporting CUDA, OpenCL, and CPU devices. This new version of ArrayFire includes several new features that improve the performance and usability for applications in machine learning, computer vision, signal processing, statistics, finance, and more. “We use ArrayFire to run the low level parallel computing layer of SDL Neural Machine Translation Products,” said William Tambellini, Senior Software Developer at SDL. “ArrayFire flexibility, robustness and dedicated support makes it a powerful tool to support the development of Deep Learning Applications.”

Call for Papers: International Workshop on Accelerators and Hybrid Exascale Systems

The eight annual  International Workshop on Accelerators and Hybrid Exascale Systems (AsHES) has issued its Call for Papers. Held in conjunction with the 32nd IEEE International Parallel and Distributed Processing Symposium, the AsHES Workshop takes place May 23 in Vancouver, Canada. “This workshop focuses on understanding the implications of accelerators and heterogeneous designs on the hardware systems, porting applications, performing compiler optimizations, and developing programming environments for current and emerging systems. It seeks to ground accelerator research through studies of application kernels or whole applications on such systems, as well as tools and libraries that improve the performance and productivity of applications on these systems.”

Intel Steps up to HPC & the Enterprise with FPGAs

In this video from the Intel HPC Developer Conference in Denver, Michael Strickland describes how Intel FPGAs are  powering new levels of performance and datacenter efficiency with FPGAs. “Altera and Intel offers a broad range of FPGA devices – from the high performaning Stratix series to the flexible MAX 10 – so you can find a device that best meets your business needs.”

SPEC/HPG hardware acceleration benchmark adds OpenMP Suite

Today SPEC’s High-Performance Group released a new version of its SPEC ACCEL software that adds a suite of OpenMP applications for measuring the performance of systems using hardware accelerator devices and supporting software. SPEC ACCEL also measures performance for computationally intensive parallel applications running under the OpenCL and OpenACC programming models.

The OpenMP application benchmarks are the first of their kind and now give our customers the opportunity to compare hardware configurations based on the most popular open-programming models,” says Guido Juckeland, SPEC/HPG vice chair. “We look forward to a wide variety of SPEC ACCEL result submissions on the SPEC website and a number of research papers comparing various optimization settings on multiple platforms.”

Creating Applications with the Intel Computer Vision SDK

“In order for developers to be able to focus on their application, a Vision Algorithm Designer application is included in the Intel Computer Vision SDK. This gives users a drag and drop interface that allows them to create new applications on the fly. Large and complex workflows can be modelled visually which takes the guesswork out of bringing together many different functions. In addition, customized code can be added to the workflows.”

GPUs Power New AWS P2 Instances for Science & Engineering in the Cloud

Today Amazon Web Services announced the availability of P2 instances, a new GPU instance type for Amazon Elastic Compute Cloud designed for compute-intensive applications that require massive parallel floating point performance, including artificial intelligence, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, genomics, and rendering. With up to 16 NVIDIA Tesla K80 GPUs, P2 instances are the most powerful GPU instances available in the cloud.

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.

Advanced Hands-On OpenCL Tutorial To Kick-Off IWOCL 2016

Registration is now open for the Advanced Hands-On OpenCL Tutorial at the IWOCL 2016 conferernce. The tutorial focuses on advanced OpenCL concepts and is an extension of the highly successful “Hands on OpenCL” course which has received over 6,500 downloads from GitHub. Simon McIntosh-Smith, Associate Professor in High Performance Computing at the University of Bristol and one of the tutorial authors will lead the sessions.

OpenMP and OpenCL on Intel Xeon Phi

“In a heterogeneous system that combines both the Intel Xeon CPU and the Intel Xeon Phi coprocessor, there are various options available to optimize applications. Whether one has an advantage over another is somewhat dependent on the application that is being run. Comparisons can be made comparing the two methods, as long as the algorithm lends itself to run and take advantage of either OpenMP or OpenCL.”

Video: Oclgrind – An Extensible OpenCL Device Simulator

“We describe Oclgrind, a platform designed to enable the creation of developer tools for analysis and debugging of OpenCL programs. Oclgrind simulates how OpenCL kernels execute with respect to the OpenCL standard, adhering to the execution and memory models that it defines. A simple plugin interface allows developer tools to observe the simulation and collect execution information to provide useful analysis, or catch bugs that would be otherwise difficult to spot when running the application on a real device. We give details about the implementation of the simulator, and describe how it can be extended with plugins that provide useful developer tools. We also present several example use-cases that have already been created using this platform, motivated by real-world problems that OpenCL developers face.”