A Look Inside China’s Chart-Topping New Supercomputer

Much to the surprise of the supercomputing community, which is gathered in Germany for the International Supercomputing Conference this morning, news arrived that a new system has dramatically topped the Top 500 list of the world’s fastest and largest machines. And like the last one that took this group by surprise a few years ago, the new system is also in China.

Recall that the reigning supercomputer in China, the Tianhe-2 machine, has stood firmly at the top of that list for three years, outpacing the U.S. “Titan” system at Oak Ridge National Laboratory. We have a more detailed analysis …

A Look Inside China’s Chart-Topping New Supercomputer was written by Nicole Hemsoth at The Next Platform.

What Will GPU Accelerated AI Lend to Traditional Supercomputing?

This week at the International Supercomputing Conference (ISC ’16) we are expecting a wave of vendors and high performance computing pros to blur the borders between traditional supercomputing and what is around the corner on the application front—artificial intelligence and machine learning.

For some, merging those two areas is a stretch, but for others, particularly GPU maker, Nvidia, which just extended its supercomputing/deep learning roadmap this morning, the story is far more direct since much of the recent deep learning work has hinged on GPUs for training of neural networks and machine learning algorithms.

We have written extensively over …

What Will GPU Accelerated AI Lend to Traditional Supercomputing? was written by Nicole Hemsoth at The Next Platform.

Framing Questions for Optimized I/O Subsystems

Building high performance systems at the bleeding edge hardware-wise without considering the way data actually moves through such a system is too common—and woefully so, given the fact that understanding and articulating an application’s requirements can lead to dramatic I/O improvements.

A range of “Frequently Unanswered Questions” are at the root of inefficient storage design due to a lack of specified workflows, and this problem is widespread, especially in verticals where data isn’t the sole business driver.

One could make the argument that data is at the heart of any large-scale computing endeavor, but as workflows change, the habit of …

Framing Questions for Optimized I/O Subsystems was written by Nicole Hemsoth at The Next Platform.

NERSC Preps for Next Generation “Cori” Supercomputer

The powerful Cori supercomputer, now being readied for deployment at NERSC (The National Energy Research Scientific Computing Center), has been named in honor of Gerty Cori. Cori was a Czech-American biochemist (August 15, 1896 – October 26, 1957) who became the first American woman to be awarded the Nobel Prize.

Cori (a.k.a. NERSC-8) is the Center’s newest supercomputer. Phase 1 of the system is currently installed with Phase 2 slated to be up and running this year.  Phase 1 is a Cray XC40 supercomputer based on the Intel Haswell multi-core processor with a theoretical peak performance of 1.92 petaflops/sec. It …

NERSC Preps for Next Generation “Cori” Supercomputer was written by Nicole Hemsoth at The Next Platform.

The Weather Company Seeks Next Data-Driven Platform

When considering system and software needs at massive scale, one application area that tends to shed light on what lies ahead is weather prediction and modeling.

Over the last year, we have had a number of pieces about what centers that deliver forecasts (and carry out research to improve those predictions) need to do to stay ahead, and while conversations about hardware and software are important, what is emerging is that weather, like many other areas of computing at scale, actually needs a platform versus innovation at one or two levels of the stack.

With that idea of a platform …

The Weather Company Seeks Next Data-Driven Platform was written by Nicole Hemsoth at The Next Platform.

What’s Fueling the Move to a Converged Data Platform?

The datacenter is going through tremendous change, and many long-held assumptions are now being called into question. Even the basic process of separating data onto a separate storage area network, growing it, and pulling it across the network and processing it, is no longer necessarily the best way to handle data. The separation between production and analytics, which has evolved into an art form, is also breaking down because it takes a day or longer to get operational data into analytic systems.

As a backdrop to all of these technology changes, organizations say they need more agility. The ability to …

What’s Fueling the Move to a Converged Data Platform? was written by Nicole Hemsoth at The Next Platform.

Former NASA Exec Brings Stealth Machine Learning Chip to Light

Chip startups come and go. Generally, we cover them because of novel architectures or potential for specific applications. But in some cases, like today, it is for those reasons and because of the people behind an effort to bring a new architecture into a crowded, and ultimately limited, landscape.

With $100 million in “patience money” from a few individual investors who believe in the future of sparse matrix-based computing on low-power and reprogrammable devices, Austin-based Knupath, has spent a decade in stealth mode designing and fabricating a custom digital signal processor (DSP) chip to target deep learning training, machine …

Former NASA Exec Brings Stealth Machine Learning Chip to Light was written by Nicole Hemsoth at The Next Platform.

Knights Landing Upgrade Will Push TACC Supercomputer to 18PF

During a trip to Dell in Austin, Texas this week, little did The Next Platform know that the hardware giant and nearby Texas Advanced Computing Center (TACC) had major news to share on the supercomputing front.

It appears the top ten-ranked Stampede supercomputer is set for an extensive, rolling upgrade—one that will keep TACC’s spot in the top tier of supercomputing sites and which will feature the latest Knights Landing processors and over time, a homogeneous Omni-Path fabric. The net effect of the upgrade will be a whopping 18 petaflops of peak performance by 2018.

The new system will begin …

Knights Landing Upgrade Will Push TACC Supercomputer to 18PF was written by Nicole Hemsoth at The Next Platform.

AWS Brings Supercomputing Set Further into Fold

Back in 2009, when yours truly was assigned the primary beat of covering supercomputing on remote hardware (then dubbed the mysterious “cloud”), the possibility that cloud-based high performance computing was little more than a pipe dream.

At that time, most scientific and technical computing communities had already developed extensive grids to extend their research beyond physical borders, and the idea of introducing new levels of latency, software, and management interfaces did not appear to be anything most HPC centers were looking forward to—even with the promise of cost-savings (as easy “bursting” was still some time off).

Just as Amazon Web …

AWS Brings Supercomputing Set Further into Fold was written by Nicole Hemsoth at The Next Platform.

Strong Scaling Key to Redrawing Neuroscience Borders

Computing for neuroscience, which has aided in our understanding of the structure and function of the brain, has been around for decades already. More recently, however, there has been neuroscience for computing, or the use of computational principles of the brain for generic data processing. For each of these neuroscience-driven areas there is a key limitation—scalability.

This is not just scalability in terms of software or hardware systems, but on the application side, limits in terms of efficiently deploying computational tools at sufficient size and time scales to yield far greater insight. While adding more compute to the problem …

Strong Scaling Key to Redrawing Neuroscience Borders was written by Nicole Hemsoth at The Next Platform.

The Age of the GPU is Upon Us

Having made the improbable jump from the game console to the supercomputer, GPUs are now invading the datacenter.  This movement is led by Google, Facebook, Amazon, Microsoft, Tesla, Baidu and others who have quietly but rapidly shifted their hardware philosophy over the past twelve months.  Each of these companies have significantly upgraded their investment in GPU hardware and in doing so have put legacy CPU infrastructure on notice.

The driver of this change has been deep learning and machine intelligence, but the movement continues to downstream into more and more enterprise-grade applications – led in part by the explosion …

The Age of the GPU is Upon Us was written by Nicole Hemsoth at The Next Platform.

The Hyperscale Effect: Tracking the Newest High-Growth IT Segment

Don’t just call it “the cloud.” Even if you think you know what cloud means, the word is fraught with too many different interpretations for too many people. Nevertheless, the effect of cloud computing, the web, and their assorted massive datacenters has had a profound impact on enterprise computing, creating new application segments and consolidating IT resources into a smaller number of mega-players with tremendous buying power and influence.

Welcome to the hyperscale market.

At the top end of the market, ten companies – behemoths like Google, Amazon, eBay, and Alibaba – each spend over $1 billion per year on …

The Hyperscale Effect: Tracking the Newest High-Growth IT Segment was written by Nicole Hemsoth at The Next Platform.

Large-Scale Weather Prediction at the Edge of Moore’s Law

Having access to fairly reliable 10-day forecasts is a luxury, but it comes with high computational costs for centers in the business of providing predictability. This ability to accurately predict weather patterns, dangerous and seasonal alike, has tremendous economic value and accordingly, significant investment goes into powering ever-more extended and on-target forecast.

What is interesting on the computational front is that the future of weather prediction accuracy, timeliness, efficiency, and scalability seems to be riding a curve not so dissimilar to that of Moore’s Law. Big leaps, followed by steady progress up the trend line, and a moderately predictable sense …

Large-Scale Weather Prediction at the Edge of Moore’s Law was written by Nicole Hemsoth at The Next Platform.

Cray Sharpens Approach to Large-Scale Graph Analytics

For those in enterprise circles who still conjure black and white images of hulking supercomputers when they hear the name “Cray,” it is worth noting that the long-standing company has done a rather successful job of shifting a critical side of its business to graph analytics and large-scale data processing.

In addition to the data-driven capabilities cooked into its XC line of supercomputers, and now with their DataWarp burst buffer adding to the I/O bottom line on supercomputers including Cori, among others, Cray has managed to take supercomputing to the enterprise big data set by blending high performance hardware with …

Cray Sharpens Approach to Large-Scale Graph Analytics was written by Nicole Hemsoth at The Next Platform.

Lustre to DAOS: Machine Learning on Intel’s Platform

Training a machine learning algorithm to accurately solve complex problems requires large amounts of data. The previous article discussed how scalable distributed parallel computing using a high-performance communications fabric like Intel Omni-Path Architecture (Intel OPA) is an essential part of what makes the training of deep learning on large complex datasets tractable in both the data center and within the cloud. Preparing large unstructured data sets for machine learning can be as intensive a task as the training process – especially for the file-system and storage subsystem(s). Starting (and restarting) big data training jobs using tens of thousands of clients …

Lustre to DAOS: Machine Learning on Intel’s Platform was written by Nicole Hemsoth at The Next Platform.

Google Takes Unconventional Route with Homegrown Machine Learning Chips

At the tail end of Google’s keynote speech at its developer conference Wednesday, Sundar Pichai, Google’s CEO mentioned that Google had built its own chip for machine learning jobs that it calls a Tensor Processing Unit, or TPU.

The boast was that the TPU offered “an order of magnitude” improvement in the performance per watt for machine learning. Any company building a custom chip for a dedicated workload is worth noting, because building a new processor is a multimillion-dollar effort when you consider hiring a design team, the cost of getting a chip to production and building the hardware and …

Google Takes Unconventional Route with Homegrown Machine Learning Chips was written by Nicole Hemsoth at The Next Platform.

IBM Extends GPU Cloud Capabilities, Targets Machine Learning

As we have noted over the last year in particular, GPUs are set for another tsunami of use cases for server workloads in high performance computing and most recently, machine learning.

As GPU maker Nvidia’s CEO stressed at this year’s GPU Technology Conference, deep learning is a target market, fed in part by a new range of their GPUs for training and executing deep neural networks, including the Tesla M40, M4, the existing supercomputing-focused K80, and now, the P100 (Nvidia’s latest Pascal processor, which is at the heart of a new appliance specifically designed for deep learning workloads).

While …

IBM Extends GPU Cloud Capabilities, Targets Machine Learning was written by Nicole Hemsoth at The Next Platform.

Climate Research Pulls Deep Learning Onto Traditional Supercomputers

Over the last year, stories pointing to a bright future for deep neural networks and deep learning in general have proliferated. However, most of what we have seen has been centered on the use of deep learning to power consumer services. Speech and image recognition, video analysis, and other features have spun from deep learning developments, but from the mainstream view, it would seem that scientific computing use cases are still limited.

Deep neural networks present an entirely different way of thinking about a problem set and the data that feeds it. While there are established approaches for images and …

Climate Research Pulls Deep Learning Onto Traditional Supercomputers was written by Nicole Hemsoth at The Next Platform.

First Burst Buffer Use at Scale Bolsters Application Performance

Over the last year, we have focused on the role burst buffer technology might play in bolstering the I/O capabilities on some of the world’s largest machines and have focused on use cases ranging from the initial target to more application-centric goals.

As we have described in discussions with the initial creator of the concept, Los Alamos National Lab’s, Gary Grider, the starting point for the technology was for moving the checkpoint and restart capabilities forward faster (detailed description of how this works here). However, as the concept developed over the years, some large supercomputing sites, including the National …

First Burst Buffer Use at Scale Bolsters Application Performance was written by Nicole Hemsoth at The Next Platform.

Can Open Source Hardware Crack Semiconductor Industry Economics?

The running joke is that when a headline begs a question, the answer is, quite simply, “No.” However, when the question is multi-layered, wrought with dependencies that stretch across an entire supply chain, user bases, and device range, and across companies in the throes of their own economic and production uncertainties, a much more nuanced answer is required.

Although Moore’s Law is not technically dead yet, organizations from the IEEE to individual device makers are already thinking their way out of a box that has held the semiconductor industry neatly for decades. However, it turns out, that thought process is …

Can Open Source Hardware Crack Semiconductor Industry Economics? was written by Nicole Hemsoth at The Next Platform.