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Unified Deep Learning Configurations and Emerging Applications

This is the final post in a five-part series from a report exploring the potential machine and a variety of computational approaches, including CPU, GPU and FGPA technologies. This article explores unified deep learning configurations and emerging applications. 

Celebrating 20 Years of the OpenMP API

“The first version of the OpenMP application programming interface (API) was published in October 1997. In the 20 years since then, the OpenMP API and the slightly older MPI have become the two stable programming models that high-performance parallel codes rely on. MPI handles the message passing aspects and allows code to scale out to significant numbers of nodes, while the OpenMP API allows programmers to write portable code to exploit the multiple cores and accelerators in modern machines.”

CIARA steps up to High Frequency Trading and Blockchain with AMD

CIARA just announced new AMD-based systems for ultra-low latency, high Frequency Trading and Blockchain solutions. “With the adoption of new technologies such as large core count processors and the usage of ECC memory, the path for all financial enterprises to reap the benefits of safe hardware acceleration without compromising reliability is getting easier,” said Patrick Scateni, Vice President of Enterprise and Performance Group at CIARA. “The joint solutions coming from the CIARA and AMD will bring high-performance and broader choice of compute platforms to the FSI market.”

DNN Implementation, Optimization, and Challenges

This is the third in a five-part series that explores the potential of unified deep learning with CPU, GPU and FGPA technologies. This post explores DNN implementation, optimization and challenges. 

Exploring the Possibilities of Deep Learning Software

This is the second post in a five-part series from a report that explores the potential of unified deep learning with CPU, GPU and FGPA technologies. This post explores the possibilities and functions of software for deep learning.

The Machine Learning Potential of a Combined Tech Approach

This is the first in a five-part series from a report exploring the potential of unified deep learning with CPU, GPU and FGPA technologies. This post explores the machine learning potential of taking a combined approach to these technologies. 

Cray Adopts AMD EPYC Processors for Supercomputing

Cray is the first system vendor to offer an optimized programing environment for AMD EYPC processors, which is a distinct advantage. “Cray’s decision to offer the AMD EPYC processors in the Cray CS500 product line expands its market opportunities by offering buyers an important new choice,” said Steve Conway, senior vice president of research at Hyperion Research.

Unified Deep Learning with CPU, GPU and FPGA Technologies

Deep learning and complex machine learning has quickly become one of the most important computationally intensive applications for a wide variety of fields. Download the new paper — from Advanced Micro Devices Inc. (AMD) and Xilinx Inc. — that explores the challenges of deep learning training and inference, and discusses the benefits of a comprehensive approach for combining CPU, GPU, FPGA technologies, along with the appropriate software frameworks in a unified deep learning architecture.

Video: The Challenge of Heterogeneous Compute & Memory Systems

Mike Ignatowski from AMD gave this talk at the Rice Oil & Gas conference. “We have reached the point where further improvements in CMOS technology and CPU architecture are producing diminishing benefits at increasing costs. Fortunately, there is a great deal of room for improvement with specialized processing, including GPUs and other emerging accelerators. In addition, there are exciting new developments in memory technology and architecture coming down the development pipeline.”

Panel Discussion: Delivering Exascale Computing for the Oil and Gas Industry

In this video from the 2018 Rice Oil & Gas Conference, Addison Snell from Intersect360 Research leads a panel discussion on Exascale computing. “High-end computing and information technology continues to stand out across the industry as a critical business enabler and differentiator with a relatively well understood return on investment. However, challenges such as constantly changing technology landscape, increasing focus on software and software innovation, and escalating concerns around workforce development still remain.”