Cray’s Steve Scott presented this talk at The Digital Future Conference. “Research and development at Cray is guided by our adaptive supercomputing vision. This vision is focused on delivering innovative, next-generation products that integrate diverse processing technologies into a unified architecture, enabling customers to surpass today’s limitations and meeting the market’s demand for realized performance.”
The inaugural Misha Mahowald Prize for Neuromorphic Engineering has been awarded to the TrueNorth project, led by Dr. Dharmendra S. Modha at IBM Research. “The Misha Mahowald Prize recognizes outstanding achievement in the field of neuromorphic engineering. Neuromorphic engineering is defined as the construction of artificial computing systems which implement key computational principles found in natural nervous systems. Understanding how to build such systems may enable a new generation of intelligent devices, able to interact in real-time in uncertain real-world conditions under severe power constraints, as biological brains do.”
Today, the National Science Foundation (NSF) announced two major awards to establish Scientific Software Innovation Institutes (S2I2). The awards, totaling $35 million over 5 years, will support the Molecular Sciences Software Institute and the Science Gateways Community Institute, both of which will serve as long-term hubs for scientific software development, maintenance and education. “The institutes will ultimately impact thousands of researchers, making it possible to perform investigations that would otherwise be impossible, and expanding the community of scientists able to perform research on the nation’s cyberinfrastructure,” said Rajiv Ramnath, program director in the Division of Advanced Cyberinfrastructure at NSF.”
Tony Hey from the Science and Technology Facilities Council presented this talk at The Digital Future conference in Berlin. “Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud computing technologies.”
“OpenPOWER is all about creating a broad ecosystem with opportunities to accelerate your workloads. For the Cognitive Cup, we provide two types of accelerators: GPUs and FPGAs. GPUs are used by the Deep Learning framework to train your neural network. When you want to use the neural network during the “classification” phase, you have a choice of Power CPUs, GPUs and FPGAs.”
Deep learning is a method of creating artificial intelligence systems that combine computer-based multi-layer neural networks with intensive training techniques and large data sets to enable analysis and predictive decision making. A fundamental aspect of deep learning environments is that they transcend finite programmable constraints to the realm of extensible and trainable systems. Recent developments in technology and algorithms have enabled deep learning systems to not only equal but to exceed human capabilities in the pace of processing vast amounts of information.
Today the FlyElephant team announced the release of the FlyElephant 2.0 platform for High Performance Computing. Versioin 2.0 enhancements include: internal expert community, collaboration on projects, public tasks, Docker and Jupyter support, a new file storage system and work with HPC clusters.
In this CCTV video, Alberto Alonso describes his new supercomputer, Breogan, that has the ability to modernize Mexico’s antiquated stock market.
Since it was launched in February, the Breogan computer has generated $475,000 for his company GACS. The algorithm it uses is much faster than the computers in Mexico’s stock exchange. “What makes the Breogan computer so unique, is that it finds attractive opportunities in the market and it buys and sells automatically when it sees a trading opportunity.”
Today Mellanox announced it has received the Award for Technology Innovation from Baidu, Inc. The award recognizes Mellanox’s achievements in designing and delivering a high-performance, low latency interconnect technology solution that positively impacts Baidu’s business. Mellanox Technologies received the award at the 2016 Baidu Datacenter Partner Conference, Baidu’s annual gathering of key datacenter partners, and was the only interconnect provider in this category.
In this special guest feature, Rob Farber writes that a study done by Kyoto University Graduate School of Medicine shows that code modernization can help Intel Xeon processors outperform GPUs on machine learning code. “The Kyoto results demonstrate that modern multicore processing technology now matches or exceeds GPU machine-learning performance, but equivalently optimized software is required to perform a fair benchmark comparison. For historical reasons, many software packages like Theano lacked optimized multicore code as all the open source effort had been put into optimizing the GPU code paths.”