Co-founder and co-editor Nicole Hemsoth brings insight from the world of high performance computing hardware and software as well as data-intensive systems and frameworks. Hemsoth is former Editor in Chief of long-standing supercomputing magazine, HPCwire. She was founding editor and conceptual creator of the data-intensive computing magazine Datanami, as well as the conceptual creator and founding Senior Editor for the large-scale infrastructure focused EnterpriseTech.
October 11, 2017 Nicole Hemsoth
One of the reasons we have written so much about Chinese search and social web giant, Baidu, in the last few years is because they have openly described both the hardware and software steps to making deep learning efficient and high performance at scale.
In addition to providing several benchmarking efforts and GPU use cases, researchers at the company’s Silicon Valley AI Lab (SVAIL) have been at the forefront of eking power efficiency and performance out of new hardware by lowering precision. This is a trend that has kickstarted similar thinking in hardware usage in other areas, including supercomputing …Read more
September 27, 2017 Nicole Hemsoth
This morning a presentation filtered from the Department of Energy’s Office of Science showing the roadmap to exascale with a 2021 machine at Argonne National Lab.
This is the Aurora machine, which had an uncertain future this year when its budgetary and other details were thrown into question. We understood the deal was being restructured and indeed it has been. The system was originally slated to appear in 2018 with 180 petaflops of peak performance at double precision floating point. Now it is 1,000 petaflops, an exascale capable machine, and will be delivered in 2021—right on target with the …Read more
September 26, 2017 Jeffrey Burt
MapR Technologies has been busy in recent years build out its capabilities as a data platform company that can support a broad range of open-source technologies, from Hadoop and Spark to Hive, and can reach from the data center through the edge and out into the cloud. At the center of its efforts is its Converged Data Platform, which comes with the MapR-FS Posix file system and includes enterprise-level database and storage that are designed to handle the emerging big data workloads.
At the Strata Data Conference in New York City Sept. 26, company officials are putting their focus …Read more
September 21, 2017 Nicole Hemsoth
The high performance computing world is set to become more diverse over the next several years on the hardware front, but for software development, this new array of ever-higher performance options creates big challenges for codes.
While the hardware advances might be moving too quick for long-standing software to take optimal advantage of, for some areas, things are at a relative standstill in terms of how to approach this future. Is it better to keep optimizing old codes that could be ticked along with the X86 tocks, or does a new architectural landscape mean starting from scratch with scientific codes–even …Read more
September 14, 2017 Nicole Hemsoth
We have heard much about the concept of dark silicon but there is a separate, related companion to this idea.
Dark bandwidth is a term that is being bandied about to describe the major inefficiencies of data movement. The idea of this is not unknown or new, but some of the ways the problem is being tackled present new practical directions as the emphasis on system balance over pure performance persists.
As ARM Research architect, Jonathan Beard describes it, the way systems work now is a lot like ordering a tiny watch battery online and having it delivered in a …Read more
September 12, 2017 Nicole Hemsoth
At well over $150,000 per appliance, the Volta GPU based DGX appliances from Nvidia, which take aim at deep learning with framework integration and 8 Volta-accelerated nodes linked with NVlink, is set to appeal to the most bleeding edge of machine learning shops.
Nvidia has built its own clusters by stringing several of these together, just as researchers at Tokyo Tech have done with the Pascal generation systems. But one of the first commercial customers for the Volta based boxes is the Center for Clinical Data Science, which is part of the first wave of hospitals set to …Read more
September 11, 2017 Glenn Lockwood
POSIX I/O is almost universally agreed to be one of the most significant limitations standing in the way of I/O performance exascale system designs push 100,000 client nodes.
The desire to kill off POSIX I/O is a commonly beaten drum among high-performance computing experts, and a variety of new approaches—ranging from I/O forwarding layers, user-space I/O stacks, and completely new I/O interfaces—are bandied about as remedies to the impending exascale I/O crisis.
However, it is much less common to hear exactly why POSIX I/O is so detrimental to scalability and performance, and what needs to change to have a suitably …Read more
August 31, 2017 Nicole Hemsoth
For a large institution playing at the leadership-class supercomputing level, NASA tends to do things a little differently than its national lab and academic peers.
One of the most striking differences between how the space agency views its supercomputing future can be found at the facilities level. Instead of building massive brick and mortar datacenters within a new or existing complex, NASA has taken the modular route, beginning with its Electra supercomputer and in the near future, with a 30 Megawatt-capable new modular installation that can house about a million compute cores.
“What we found is that the modular approach …Read more
August 28, 2017 Ken Strandberg
We continue with our second part of the series on the Tsubame supercomputer (first section here) with the next segment of our interview with Professor Satoshi Matsuoka, of the Tokyo Institute of Technology (Tokyo Tech).
Matsuoka researches and designs large scale supercomputers and similar infrastructures. More recently, he has worked on the convergence of Big Data, machine/deep learning, and AI with traditional HPC, as well as investigating the post-Moore technologies towards 2025. He has designed supercomputers for years and has collaborated on projects involving basic elements for the current and more importantly future exascale systems.
TNP: Will you be running …Read more
August 23, 2017 Nicole Hemsoth
Propping up a successful silicon startup is no simple feat, but venture-backed Wave Computing has managed to hold its own in the small but critical AI training chip market–so far.
Seven years after its founding and the company’s early access program for beta machines based on its novel DPU manycore architecture is now open, which is prompting Wave to be more forthcoming about the system and chip architecture for deep learning-focused dataflow architecture.
Dr. Chris Nicol, Wave Computing CTO and lead architect of the Dataflow Processing Unit (DPU) admitted to the crowd at Hot Chips this week that maintaining funding …Read more