The Tokyo-based National Institute of Advanced Industrial Science and Technology (AIST) is taking bids for a new supercomputer that will deliver more than 130 half precision petaflops when completed in late 2017. The system, known as the AI Bridging Cloud Infrastructure (ABCI), is mainly being built for artificial intelligence developers and providers, and will be made available as a cloud resource to researchers and commercial organizations.
At Intel’s recent AI Day, the chipmaker previewed a series of future products that it intends to use to unseat GPUs as the de facto standard for machine learning. The one-day event was Intel’s most assertive pronouncement of its intentions to become a major player in the artificial intelligence market.
The new Green500 list of the most energy-efficient supercomputers demonstrates some significant progress from last year. Thanks to the new manycore processors from Intel and NVIDIA that are starting to penetrate the top systems, performance per watt numbers are on the rise.
At SC16, during a birds-of-a-feather (BoF) session held Wednesday afternoon, a room full of supercomputing enthusiasts listened attentively to the latest developments at the Exascale Computing Project (ECP). Department of Energy (DOE) representatives were on hand to deliver updates on the software and hardware efforts that the project is undertaking.
Although Intel had no blockbuster reveals at this year’s supercomputing conference (SC16), they did issue a flurry of announcements to remind everyone that they still dominate much of the componentry in the HPC industry. And if anything, they are looking to extend their hegemony, as well as move into new areas.
Just as the choice of processors architectures in supercomputing is expanding with GPUs, FPGAs, ARM and Power, memory is beginning to diversify as well. Novel technologies like 3D XPoint, resistive RAM/memristors, and 3D memory stacks are already starting to work their way into the hands of HPC users. At SC16 this week in Salt Lake City, one of the Friday panels, “The Future of Memory Technology for Exascale and Beyond IV,” will delve into this subject more deeply.
The rollout of 200 Gbps networking began in earnest this week with Mellanox’s unveiling of its initial HDR InfiniBand portfolio of Quantum switches, ConnectX-6 adapters, and LinkX cables. Although none of the products will be available until 2017, the imminent move to 200 Gbps is set to leapfrog the competition, in particular, Intel, with its current 100 Gbps Omni-Path technology.
The prospect of FPGA-powered supercomputing has never looked brighter. The availability of more performant chips, the maturation of the OpenCL toolchain, the acquisition of Altera by Intel, and the world’s largest deployment of FPGAs in the datacenter by Microsoft, suggest that reconfigurable computing may finally fulfill its promise as a major technology for high performance computing.
In what seems paradoxical, a group of computer scientists have demonstrated that reducing the mathematical precision in a supercomputing computation can actually lead to more accurate solutions. The premise of the technique is to apply the energy savings reaped from lower precision calculations toward additional computation that will improve the quality of the results.
AI startup Graphcore has emerged from stealth mode with the announcement of $30 million in initial Series A funding. The Bristol, UK-based company will use the cash infusion to complete development of its Intelligent Processing Unit (IPU), a custom-built chip aimed at machine learning workloads. The funding was led by Robert Bosch Venture Capital GmbH and Samsung Catalyst Fund; also joining were Amadeus Capital Partners, C4 Ventures, Draper Esprit plc, Foundation Capital and Pitango Venture Capital.