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Supermicro Rolls Out New Servers with Tesla P100 GPUs

“Our high-performance computing solutions enable deep learning, engineering, and scientific fields to scale out their compute clusters to accelerate their most demanding workloads and achieve fastest time-to-results with maximum performance per watt, per square foot, and per dollar,” said Charles Liang, President and CEO of Supermicro. “With our latest innovations incorporating the new NVIDIA P100 processors in a performance and density optimized 1U and 4U architectures with NVLink, our customers can accelerate their applications and innovations to address the most complex real world problems.”

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.

E4 Computer Engineering Rolls Out GPU-accelerated OpenPOWER server

“The POWER8 with NVIDIA NVLink processor enables incredible speed of data transfer between CPUs and GPUs ideal for emerging workloads like AI, machine learning and advanced analytics”, said Rick Newman, Director of OpenPOWER Strategy & Market Development Europe. “The open and collaborative spirit of innovation within the OpenPOWER Foundation enables companies like E4 to leverage new technology and build cutting edge solutions to help clients grappling with the massive amounts of data in today’s technology environment.”

Nvidia Releases Cuda 8

Today Nvidia announced the general availability of CUDA 8 toolkit for GPU developers. “A crucial goal for CUDA 8 is to provide support for the powerful new Pascal architecture, the first incarnation of which was launched at GTC 2016: Tesla P100,” said Nvidia’s Mark Harris in a blog post. “One of NVIDIA’s goals is to support CUDA across the entire NVIDIA platform, so CUDA 8 supports all new Pascal GPUs, including Tesla P100, P40, and P4, as well as NVIDIA Titan X, and Pascal-based GeForce, Quadro, and DrivePX GPUs.”

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.

Video: Nvidia Unveils ARM-Powered SoC with Volta GPU

Today at GTC Europe, Nvidia unveiled Xavier, an all-new SoC based on the company’s next-gen Volta GPU, which will be the processor in future self-driving cars. According to Huang, the ARM-based Xavier will feature unprecedented performance and energy efficiency, while supporting deep-learning features important to the automotive market. A single Xavier-based AI car supercomputer will be able to replace today’s fully configured DRIVE PX 2 with two Parker SoCs and two Pascal GPUs.

Baidu Research Announces DeepBench Benchmark for Deep Learning

“Deep learning developers and researchers want to train neural networks as fast as possible. Right now we are limited by computing performance,” said Dr. Diamos. “The first step in improving performance is to measure it, so we created DeepBench and are opening it up to the deep learning community. We believe that tracking performance on different hardware platforms will help processor designers better optimize their hardware for deep learning applications.”

Register Now for GPU Mini-Hackathon at ORNL Nov. 1-3

Oak Ridge National Lab is hosting a 3-day GPU Mini-hackathon led by experts from the OLCF and Nvidia. The event takes place Nov. 1-3 in Knoxville, Tennessee. “General-purpose Graphics Processing Units (GPGPUs) potentially offer exceptionally high memory bandwidth and performance for a wide range of applications. The challenge in utilizing such accelerators has been the difficulty in programming them. This event will introduce you to GPU programming techniques.”

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.

Video: The Deep Learning AI Revolution

In this video from GTC 2016 in Taiwan, Nvidia CEO Jen-Hsun Huang unveils technology that will accelerate the deep learning revolution that is sweeping across industries. “AI computing will let us create machines that can learn and behave as humans do. It’s the reason why we believe this is the beginning of the age of AI.”