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In-Memory Neural Net Chip Cuts Data Movement
October 8, 2018
A university-industry research team is reporting a performance advance for neural networks with the development of a chip with potential applications for image recognition in autonomous vehicles and robots. The chip design relies on in-memory processing and the replacement of standard transistors with capacitors used to store electrical charges. Read more…
NIST Photonics Chip Breaks New Ground and Models Neural Net
August 7, 2018
Researchers at the National Institute of Standards and Technology (NIST) have made a silicon chip that distributes optical signals precisely across a miniature Read more…
Intel Pledges First Commercial Nervana Product ‘Spring Crest’ in 2019
May 24, 2018
At its AI developer conference in San Francisco yesterday, Intel embraced a holistic approach to AI and showed off a broad AI portfolio that includes Xeon processors, Movidius technologies, FPGAs and Intel’s Nervana Neural Network Processors (NNPs), based on the technology it acquired in 2016. Read more…
AI Self-Training Goes Forward at Google DeepMind
October 19, 2017
DeepMind, Google’s AI research organization, announced today in a blog that AlphaGo Zero, the latest evolution of AlphaGo (the first computer program to defeat a Go world champion) trained itself within three days to play Go at a superhuman level (i.e., better than any human) – and to beat the old version of AlphaGo – without leveraging human expertise, data or training. Read more…
AI Speeds Astrophysics Image Analysis by 10,000x
September 3, 2017
Since their earliest days, humans have gazed with wonder upon the firmaments and sought to understand the secrets of the heavenly canopy. In the late 20th centu Read more…
Here’s What a Neural Net Looks Like On the Inside
February 15, 2017
Ever wonder what the inside of a machine learning model looks like? Today Graphcore released fascinating images that show how the computational graph concept ma Read more…
AI’s Forward March: Machine Teaches Itself to Play Chess in 72 Hours
September 23, 2015
The field of artificial intelligence has had a rocky history with numerous setbacks, but there have been high points too, like when IBM's Deep Blue beat reignin Read more…
IARPA Seeks Partners in Brain-Inspired AI Initiative
January 22, 2015
US intelligence officials have set in motion a five-year project to spark progress in machine learning by reverse-engineering the algorithms of the human brain. Read more…
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Whitepaper
A New Standard in CAE Solutions for Manufacturing
Today, manufacturers of all sizes face many challenges. Not only do they need to deliver complex products quickly, they must do so with limited resources while continuously innovating and improving product quality. With the use of computer-aided engineering (CAE), engineers can design and test ideas for new products without having to physically build many expensive prototypes. This helps lower costs, enhance productivity, improve quality, and reduce time to market.
As the scale and scope of CAE grows, manufacturers need reliable partners with deep HPC and manufacturing expertise. Together with AMD, HPE provides a comprehensive portfolio of high performance systems and software, high value services, and an outstanding ecosystem of performance optimized CAE applications to help manufacturing customers reduce costs and improve quality, productivity, and time to market.
Read this whitepaper to learn how HPE and AMD set a new standard in CAE solutions for manufacturing and can help your organization optimize performance.
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Sponsored by HPE
Whitepaper
Porting CUDA Applications to Run on AMD GPUs
A workload-driven system capable of running HPC/AI workloads is more important than ever. Organizations face many challenges when building a system capable of running HPC and AI workloads. There are also many complexities in system design and integration. Building a workload driven solution requires expertise and domain knowledge that organizational staff may not possess.
This paper describes how Quanta Cloud Technology (QCT), a long-time Intel® partner, developed the Taiwania 2 and Taiwania 3 supercomputers to meet the research needs of the Taiwan’s academic, industrial, and enterprise users. The Taiwan National Center for High-Performance Computing (NCHC) selected QCT for their expertise in building HPC/AI supercomputers and providing worldwide end-to-end support for solutions from system design, through integration, benchmarking and installation for end users and system integrators to ensure customer success.
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Sponsored by AMD
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