IBM has created a virtual hackathon for all you lovely developers to test drive your data-intensive applications on the OpenPOWER server, GPU and accelerator platform. And there’s $27,000 worth of prizes on the table. Want to give it a go? Check out the competition rules and register for the OpenPOWER Developer Challenge.
The closing deadline is September 1 and already 277 individuals have signed up. So don’t dilly dally: tear down those hardware performance barriers and submit your entry. Choose which track is the one for you and connect with the experts ‘round the clock on Slack to get …
OpenPower Developers Primed for Big Wins at IBM Hackathon was written by Nicole Hemsoth at The Next Platform.
Sometimes, it seems that people are of two minds about high performance computing. They want it to be special and distinct from the rest of the broader IT market, and at the same time they want the distributed simulation and modeling workloads that have for decades been the most exotic things around to be so heavily democratized that they become pervasive. Democratized. Normal.
We are probably a few years off from HPC reaching this status, but this is one of the goals that the new HPC team at Dell has firmly in mind as the world’s second largest system maker …
When HPC Becomes Normal was written by Timothy Prickett Morgan at The Next Platform.
If money was no object, then arguably the major nations of the world that always invest heavily in supercomputing would have already put an exascale class system into the field. But money always matters and ultimately supercomputers have to justify their very existence by enabling scientific breakthroughs and enhancing national security.
This, perhaps, is why the Exascale Computing Project establish by the US government last summer is taking such a measured pace in fostering the technologies that will ultimately result in bringing three exascale-class systems with two different architectures into the field after the turn of the next decade. The …
Stretching Software Across Future Exascale Systems was written by Timothy Prickett Morgan at The Next Platform.
The supercomputing industry is as insatiable as it is dreamy. We have not even reached our ambitions of hitting the exascale level of performance in a single system by the end of this decade, and we are stretching our vision out to the far future and wondering how the capacity of our largest machines will scale by many orders of magnitude more.
Dreaming is the foundation of the technology industry, and supercomputing has always been where the most REM action takes place among the best and brightest minds in computing, storage, and networking – as it should be. But to …
Dreaming Of 100 Exaflops In 2030 was written by Timothy Prickett Morgan at The Next Platform.
As supercomputers expand in terms of processing, storage, and network capabilities, the size and scope of simulations is also expanding outward. While this is great news for scientific progress, this naturally creates some new bottlenecks, particularly on the analysis and visualization fronts.
Historically, most large-scale simulations would dump time step and other data at defined intervals onto disk for post-processing and visualization, but as the petabyte scale of that process adds more weight, that is becoming less practical. Further, for those who know what they want to find in that data, using an in situ approach to finding the answer …
In Situ Analysis to Push Supercomputing Efficiency was written by Nicole Hemsoth at The Next Platform.
As the world is now aware, China is now home to the world’s most powerful supercomputer, toppling the previous reigning system, Tianhe-2, which is also located in the country.
In the wake of the news, we took an in-depth look at the architecture of the new Sunway TiahuLight machine, which will be useful background as we examine a few of the practical applications that have been ported to and are now running on the 10 million-core, 125 petaflop-capable supercomputer.
The sheer size and scale of the system is what initially grabbed headlines when we broke news about the system last …
Inside Look at Key Applications on China’s New Top Supercomputer was written by Nicole Hemsoth at The Next Platform.
It is an accepted principle of modern infrastructure that at a certain scale, customization like that done by Google, Amazon Web Services, Microsoft, or Baidu pays off. While Oracle is building its own public cloud, it does not have the kind of scale that these companies do, but it does have something else that warrants customization and co-design up and down its stack: more than 420,000 customers who generate $38.5 billion in sales.
This, in a nutshell, is why Oracle continues to invest in its Sparc processors even though many of its customers deploy Oracle’s middleware, database, and application software …
Oracle Takes On Xeons With Sparc S7 was written by Timothy Prickett Morgan at The Next Platform.
System software setup and maintenance has become a major efficiency drag on HPC labs and OEMs alike, but community and industry efforts are now underway to reduce the huge amounts of duplicated development, validation and maintenance work across the HPC ecosystem. Disparate efforts and approaches, while necessary on some levels, slow adoption of hardware innovation and progress toward exascale performance. They also complicate adoption of complex workloads like big data and machine learning.
With the creation of the OpenHPC Community, a Linux Foundation collaborative project, the push is on to minimize duplicated efforts in the HPC software stack wherever …
System Software, Orchestration Gets an OpenHPC Boost was written by Nicole Hemsoth at The Next Platform.
In the last couple of years, we have written and heard about the usefulness of GPUs for deep learning training as well as, to a lesser extent, custom ASICs and FPGAs. All of these options have shown performance or efficiency advantages over commodity CPU-only approaches, but programming for all of these is often a challenge.
Programmability hurdles aside, deep learning training on accelerators is standard, but is often limited to a single choice—GPUs or, to a far lesser extent, FPGAs. Now, a research team from the University of California Santa Barbara has proposed a new middleware platform that can combine …
Emerging “Universal” FPGA, GPU Platform for Deep Learning was written by Nicole Hemsoth at The Next Platform.
When IBM sold off its System x division to Lenovo Group in the fall of 2014, some big supercomputing centers in the United States and Europe that were long-time customers of Big Blue had to stop and think about what their future systems would look like and who would supply them. It was not a foregone conclusion that the Xeon-based portion of IBM’s HPC business would just move over to Lenovo as part of the sale.
Quite the opposite, in fact. Many believed that Lenovo could not hold onto its HPC business, and Hewlett Packard Enterprise and Dell were quick …
Lenovo HPC Bounces Back After IBM Spinoff was written by Timothy Prickett Morgan at The Next Platform.
Weather modeling and forecasting centers are among some of the top users of supercomputing systems and are at the top of the list when it comes to areas that could benefit from exascale-class compute power.
However, for modeling centers, even those with the most powerful machines, there is a great deal of leg work on the code front in particular to scale to that potential. Still, many, including most recently the UK Met Office, have planted a stake in the ground for exascale—and they are looking beyond traditional architectures to meet the power and scalability demands they’ll be facing …
Novel Architectures on the Far Horizon for Weather Prediction was written by Nicole Hemsoth at The Next Platform.
When supercomputer maker SGI tweaked its NUMA server technology to try to pursue sales in the datacenter, the plan was not to go it alone but rather to partner with the makers of workhorse Xeon servers that did not – and would not – make their own big iron but who nonetheless want to sell high-end machines to their customers.
This, company officials have said all along, is the only way that SGI, which is quite a bit smaller than many of the tier one server makers, can reach the total addressable market that the company has forecast for its …
Cisco Connects With SGI For Big NUMA Iron was written by Timothy Prickett Morgan at The Next Platform.
Converged systems are a hot commodity in the IT sector these days. But it looks to us like the hype over various kinds of integrated systems that weld servers and storage together into preconfigured stacks including hyperconverged stacks that literally merge the compute and storage layers on the same servers – is just a bit bigger than the appetite for such iron in the datacenters of the world.
According to the latest statistics from IDC, the market for converged systems, which is a broader definition of such machines that includes integrated systems, certified reference systems, and hyperconverged systems, the market …
The Hype About Converged Systems was written by Timothy Prickett Morgan at The Next Platform.
Since the 1990s, MPI (Message Passing Interface) has been the dominant communications protocol for high-performance scientific and commercial distributed computing. Designed in an era when processors with two or four cores were considered high-end parallel devices, the recent move to processors containing tens to a few hundred cores (as exemplified by the current Intel Xeon and Intel Xeon Phi processor families) has exacerbated scaling issues inside MPI itself. Increased network traffic, amplified by high performance communications fabrics such as InfiniBand and Intel Omni-Path Architecture (Intel OPA) manifest an MPI performance and scaling issue.
In recognition of their outstanding research and …
Mitigating MPI Message Matching Issues was written by Nicole Hemsoth at The Next Platform.
We don’t have a Moore’s Law problem so much as we have a materials science or alchemy problem. If you believe in materials science, what seems abundantly clear in listening to so many discussions about the end of scale for chip manufacturing processes is that, for whatever reason, the industry as a whole has not done enough investing to discover the new materials that will allow us to enhance or move beyond CMOS chip technology.
The only logical conclusion is that people must actually believe in alchemy, that some kind of magic is going to save the day and allow …
Alchemy Can’t Save Moore’s Law was written by Timothy Prickett Morgan at The Next Platform.
The rumors that supercomputer maker Fujitsu would be dropping the Sparc architecture and moving to ARM cores for its next generation of supercomputers have been going around since last fall, and at the International Supercomputing Conference in Frankfurt, Germany this week, officials at the server maker and RIKEN, the research and development arm of the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) that currently houses the mighty K supercomputer, confirmed that this is indeed true.
The ARM architecture now gets a heavy-hitter system maker with expertise in developing processors to support diverse commercial and technical workloads, and …
Inside Japan’s Future Exascale ARM Supercomputer was written by Timothy Prickett Morgan at The Next Platform.
As we have written about extensively here at The Next Platform, there is no shortage of use cases in deep learning and machine learning where HPC hardware and software approaches have bled over to power next generation applications in image, speech, video, and other classification and learning tasks.
Since we focus on high performance computing systems here in their many forms, that trend has been exciting to follow, particularly watching GPU computing and matrix math-based workloads find a home outside of the traditional scientific supercomputing center.
This widened attention has been good for HPC as well since it has …
HPC is Great for AI, But What Does Supercomputing Stand to Gain? was written by Nicole Hemsoth at The Next Platform.
Sales of HPC systems were a lot brisker in 2015 than anticipated, and according to the latest prognostications from the market researchers at IDC presented from the International Supercomputing Conference in Frankfurt, Germany this week, growth in the HPC sector will continue to outpace that of the overall IT market for many years to come.
In a sense, the good numbers that the HPC market turned in last year are perhaps a little undercounted. In his traditional early morning breakfast briefing at the conference, Earl Joseph, program vice president for high performance computing at IDC, said that he had been …
HPC Spending Outpaces The IT Market, And Will Continue To was written by Timothy Prickett Morgan at The Next Platform.
When we cover the bi-annual listing of the world’s most powerful supercomputers, the metric at the heart of those results, the high performance Linpack benchmark, the gold standard for over two decades, is the basis. However, many have argued the benchmark is getting long in tooth with its myopic focus on sheer floating point performance over other important factors that determine a supercomputer’s value for real-world applications.
This shift in value stands to reason, since larger machines mean more data coursing through the system, thus an increased reliance on memory and the I/O subsystem, among other factors. While raw floating …
Measuring Top Supercomputer Performance in the Real World was written by Nicole Hemsoth at The Next Platform.
Intel has finally opened the first public discussions of its investment in the future of machine learning and deep learning and while some might argue it is a bit late in the game with its rivals dominating the training market for such workloads, the company had to wait for the official rollout of Knights Landing and extensions to the scalable system framework to make it official—and meaty enough to capture real share from the few players doing deep learning at scale.
Yesterday, we detailed the announcement of the first volume shipments of Knights Landing, which already is finding a home …
Knights Landing Proves Solid Ground for Intel’s Stake in Deep Learning was written by Nicole Hemsoth at The Next Platform.