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CUDA-X HPC: Libraries and Tools for your Next Scientific Breakthrough

Today NVIDIA announced CUDA-X HPC, a collection of libraries, tools, compilers and APIs that helps developers solve the world’s most challenging problems. “CUDA-X HPC includes highly tuned kernels essential for high-performance computing. GPU-accelerated libraries for linear algebra, parallel algorithms, signal and image processing lay the foundation for compute-intensive applications in areas such as computational physics, chemistry, molecular dynamics, and seismic exploration.”

NVIDIA Brings CUDA to Arm for HPC

Today NVIDIA announced its support for Arm CPUs, providing the high performance computing industry a new path to build extremely energy-efficient, AI-enabled exascale supercomputers. “NVIDIA is making available to the Arm ecosystem its full stack of AI and HPC software — which accelerates more than 600 HPC applications and all AI frameworks — by year’s end. The stack includes all NVIDIA CUDA-X AI and HPC libraries, GPU-accelerated AI frameworks and software development tools such as PGI compilers with OpenACC support and profilers.”

Video: NVIDIA Rolls out TensorRT Hyperscale Platform and New T4 GPU for Ai Datacenters

This morning at GTC Japan, NVIDIA CEO Jensen Huang announced a set new products centered around Ai and accelerated computing. Targeting Hyperscale datacenters looking to run Ai workloads, NVIDIA continues to innovate Machine Learning technologies at an unprecedented pace. “There is no question that deep learning-powered AI is being deployed around the world, and we’re seeing incredible growth here,” Huang told an audience of more than 4,000 press, partners, academics and technologists gathered on the latest stop in a GTC world tour.

The Simulation of the Behavior of the Human Brain using CUDA

Pedro Valero-Lara from BSC gave this talk at the GPU Technology Conference. “The attendees can learn about how the behavior of Human Brain is simulated by using current computers, and the different challenges which the implementation has to deal with. We cover the main steps of the simulation and the methodologies behind this simulation. In particular we highlight and focus on those transformations and optimizations carried out to achieve a good performance on NVIDIA GPUs.”

Inside the Volta GPU Architecture and CUDA 9

“This presentation will give an overview about the new NVIDIA Volta GPU architecture and the latest CUDA 9 release. The NVIDIA Volta architecture powers the worlds most advanced data center GPU for AI, HPC, and Graphics. Volta features a new Streaming Multiprocessor (SM) architecture and includes enhanced features like NVLINK2 and the Multi-Process Service (MPS) that delivers major improvements in performance, energy efficiency, and ease of programmability. You”ll learn about new programming model enhancements and performance improvements in the latest CUDA9 release.”

NVIDIA Releases Cuda 9.2 for GPU Code Acceleration

Today NVIDIA released Cuda 9.2, which includes updates to libraries, a new library for accelerating custom linear-algebra algorithms, and lower kernel launch latency. “CUDA 9 is the most powerful software platform for GPU-accelerated applications. It has been built for Volta GPUs and includes faster GPU-accelerated libraries, a new programming model for flexible thread management, and improvements to the compiler and developer tools. With CUDA 9 you can speed up your applications while making them more scalable and robust.”

Call for Applications: NCSA GPU Hackathon in September

NCSA is now accepting team applications for the Blue Waters GPU Hackathon. This event will take place September 10-14, 2018 in Illinois. “General-purpose Graphics Processing Units (GPGPUs) potentially offer exceptionally high memory bandwidth and performance for a wide range of applications. A challenge in utilizing such accelerators has been learning how to program them. These hackathons are intended to help overcome this challenge for new GPU programmers and also to help existing GPU programmers to further optimize their applications – a great opportunity for graduate students and postdocs. Any and all GPU programming paradigms are welcome.”

Altair acquires FluiDyna CFD Technology for GPUs

Altair has acquired Germany-based FluiDyna GmbH, a renowned developer of NVIDIA CUDA and GPU-based Computational Fluid Dynamics (CFD) and numerical simulation technologies in whom Altair made an initial investment in 2015. FluiDyna’s simulation software products ultraFluidX and nanoFluidX have been available to Altair’s customers through the Altair Partner Alliance and also offered as standalone licenses. “We are excited about FluiDyna and especially their work with NVIDIA technology for CFD applications,” said James Scapa, Founder, Chairman, and CEO at Altair. “We believe the increased throughput and lower cost of GPU solutions is going to allow for a significant increase in simulations which can be used to further impact the design process.”

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.”

Bright Computing Release 8.1 adds new features for Deep Learning, Kubernetes, and Ceph

Today Bright Computing released version 8.1 of the Bright product portfolio with new capabilities for cluster workload accounting, cloud bursting, OpenStack private clouds, deep learning, AMD accelerators, Kubernetes, Ceph, and a new lightweight daemon for monitoring VMs and non-Bright clustered nodes. “The response to our last major release, 8.0, has been tremendous,” said Martijn de Vries, Chief Technology Officer of Bright Computing. “Version 8.1 adds many new features that our customers have asked for, such as better insight into cluster utilization and performance, cloud bursting, and more flexibility with machine learning package deployment.”