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 30, 2017 Nicole Hemsoth
GPU accelerated supercomputing is not a new phenomenon with many high performance computing codes already primed to run on Nvidia hardware in particular.
However, for some legacy codes with special needs (changing models, high computational demands), particularly in areas like weather, the gap between those codes and the promise of GPU acceleration is rather large, even with higher level tools like OpenACC to bridge the divide—all without major code rewrites.
Given the limitations of porting some legacy Fortran codes to GPUs, a research team Tokyo Tech has devised what it calls, “hybrid Fortran” which is designed to “increase productivity when …Read more
October 30, 2017 Nicole Hemsoth
Although much of the attention around deep learning for voice has focused on speech recognition, developments in artificial speech synthesis (text to speech) based on neural network approaches have been just as swift.
The goal with text-to-speech (TTS), as in other voice-related deep learning areas, is to get the training and inference times way down to allow for fast delivery of services and low power consumption and utilization of hardware resources. A recent effort at Chinese search giant, Baidu, which is at often at the forefront of deep learning for voice recognition and TTS, has shown remarkable progress on both …Read more
October 27, 2017 Nicole Hemsoth
For quantum computing to make the leap from theory and slim early use cases to broader adoption, a programmability jump is required. Some of the first hurdles have been knocked over in the last few weeks with new compiler and API-based development efforts that abstract some of the complex physics required for both qubit and gate-based approaches to quantum devices.
The more public recent effort was the open source publication of OpenFermion, a quantum compiler based on work at Google and quantum startup, Rigetti Computing, that is focused on applications in quantum chemistry and materials science. OpenFermion is …Read more
October 23, 2017 Nicole Hemsoth
Supercomputer maker Cray is always looking for ways to extend its reach outside of the traditional academic and government markets where the biggest deals are often made.
From its forays into graph analytics appliances and more recently, machine and deep learning, the company has potential to exploit its long history building some of the world’s fastest machines. This has expanded into some new ventures wherein potential new Cray users can try on the company’s systems, including via an on-demand partnership with datacenter provider, Markley, and now, inside of Microsoft’s Azure datacenters.
For Microsoft Azure cloud users looking to bolster modeling …Read more
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