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InfiniBand And Proprietary Networks Still Rule Real HPC

With the network comprising as much as a quarter of the cost of a high performance computing system and being absolutely central to the performance of applications running on parallel systems, it is fair to say that the choice of network is at least as important as the choice of compute engine and storage hierarchy. That’s why we like to take a deep dive into the networking trends present in each iteration of the Top 500 supercomputer rankings as they come out.

It has been a long time since the Top 500 gave a snapshot of pure HPC centers that

InfiniBand And Proprietary Networks Still Rule Real HPC was written by Timothy Prickett Morgan at The Next Platform.

Fix Your NAS With Metadata

Enterprises are purchasing storage by the truckload to support an explosion of data in the datacenter. IDC reports that in the first quarter of 2017, total capacity shipments were up 41.4 percent year-over-year and reached 50.1 exabytes of storage capacity shipped. As IT departments continue to increase their spending on capacity, few realize that their existing storage is a pile of gold that can be fully utilized once enterprises overcome the inefficiencies created by storage silos.

A metadata engine can virtualize the view of data for an application by separating the data (physical) path from the metadata (logical) path. This

Fix Your NAS With Metadata was written by Timothy Prickett Morgan at The Next Platform.

Momentum is Building for ARM in HPC

2011 marked ARM’s first step into the world of HPC with the European Mont-Blanc project. The premise was simple: leverage the energy efficiency of ARM-based mobile designs for high performance computing applications.

Unfortunately, making the leap from the mobile market to HPC was not an easy feat. Long time players in this space, such as Intel and IBM, hold home field advantage: that of legacy software. HPC-optimized libraries, compilers and applications were already present for these platforms. This was not, however, the case for ARM. Early adopters had to start, largely from scratch, porting and building an ecosystem with a

Momentum is Building for ARM in HPC was written by Nicole Hemsoth at The Next Platform.

A Deep Learning Performance Lens for Low Precision Inference

Few companies have provided better insight into how they think about new hardware for large-scale deep learning than Chinese search giant, Baidu.

As we have detailed in the past, the company’s Silicon Valley Research Lab (SVAIL) in particular has been at the cutting edge of model development and hardware experimentation, some of which is evidenced in their publicly available (and open source) DeepBench deep learning benchmarking effort, which allowed users to test different kernels across various hardware devices for training.

Today, Baidu SVAIL extended DeepBench to include support for inference as well as expanded training kernels. Also of

A Deep Learning Performance Lens for Low Precision Inference was written by Nicole Hemsoth at The Next Platform.

Giving Out Grades For Exascale Efforts

Just by being the chief architect of the IBM’s BlueGene massively parallel supercomputer, which was built as part of a protein folding simulation grand challenge effort undertaken by IBM in the late 1990s, Al Gara would be someone whom the HPC community would listen to whenever he spoke. But Gara is now an Intel Fellow and also chief exascale architect at Intel, which has emerged as the second dominant supplier of supercomputer architectures alongside Big Blue’s OpenPower partnership with founding members Nvidia, Mellanox Technologies, and Google.

It may seem ironic that Gara did not stay around IBM to help this

Giving Out Grades For Exascale Efforts was written by Timothy Prickett Morgan at The Next Platform.

U.S. Military Sees Future in Neuromorphic Computing

The novel architectures story is still shaping out for 2017 when it comes machine learning, hyperscale, supercomputing and other areas.

From custom ASICs at Google, new uses for quantum machines, FPGAs finding new routes into wider application sets, advanced GPUs primed for deep learning, hybrid combinations of all of the above, it is clear there is serious exploration of non-CMOS devices. When the Department of Energy in the U.S. announced its mission to explore novel architectures, one of the clear candidates for investment appeared to be neuromorphic chips—efficient pattern matching devices that are in development at Stanford (NeuroGrid), The

U.S. Military Sees Future in Neuromorphic Computing was written by Nicole Hemsoth at The Next Platform.

Machine Learning and the Language of the Brain

For years, researchers have been trying to figure out how the human brain organizes language – what happens in the brain when a person is presented with a word or an image. The work has academic rewards of its own, given the ongoing push by researchers to better understand the myriad ways in which the human brain works.

At the same time, ongoing studies can help doctors and scientists learn how to better treat people with aphasia or other brain disorders caused by strokes, tumors or trauma that impair a person’s ability to communicate – to speak, read, write and

Machine Learning and the Language of the Brain was written by Nicole Hemsoth at The Next Platform.

Exascale on the Far Horizon for Cash-Strapped Oil and Gas

All the compute power in the world is useless against code that cannot scale. And neither compute or code can be useful if growing data for simulations cannot be collected and managed.

But ultimately, none of this is useful at all if the industry that needs these HPC resources is having more trouble than ever acquiring them. It comes as no surprise that the national labs and major research centers will be the first to get exaflop-capable systems, but in a normal market (like the one oil and gas knew not long ago) these machines would be relatively quickly followed

Exascale on the Far Horizon for Cash-Strapped Oil and Gas was written by Nicole Hemsoth at The Next Platform.

Casing The HPC Market Is Hard, And Getting Harder

Markets are always changing. Sometimes information technology is replaced by a new thing, and sometimes it morphs from one thing to another so gradually that is just becomes computing or networking or storage as we know it. For instance, in the broadest sense, all infrastructure will be cloudy, even if it is bare metal machines or those using containers or heavier server virtualization. In a similar way, in the future all high performance computing may largely be a kind of artificial intelligence, bearing little resemblance to the crunch-heavy simulations we are used to.

It has taken two decades for cloud

Casing The HPC Market Is Hard, And Getting Harder was written by Timothy Prickett Morgan at The Next Platform.

The Biggest Shift in Supercomputing Since GPU Acceleration

For years, the pace of change in large-scale supercomputing neatly tracked with the curve of Moore’s Law. As that swell flattens, and as the competitive pressure ticks up to build productive exascale supercomputers in the next few years, HPC has been scrambling to find the silver bullet architecture to reach sustained exascale performance. And as it turns out, there isn’t one.

But there is something else—something few saw coming three years ago, has less to do with hardware than it does a shift in how we approach massive-scale simulations, and is happening so fast that too-far-ahead-of-time procurements are

The Biggest Shift in Supercomputing Since GPU Acceleration was written by Nicole Hemsoth at The Next Platform.

Thinking Through The Cognitive HPC Nexus With Big Blue

There are plenty of things that the members of the high performance community do not agree on, there is a growing consensus that machine learning applications will at least in some way be part of the workflow at HPC centers that do traditional simulation and modeling.

Some HPC vendors think the HPC and AI systems have either already converged or will soon do so, and others think that the performance demands (both in terms of scale and in time to result) on both HPC and AI will necessitate radically different architectures and therefore distinct systems for these two workloads. IBM,

Thinking Through The Cognitive HPC Nexus With Big Blue was written by Timothy Prickett Morgan at The Next Platform.

Competition Returns To X86 Servers In Epyc Fashion

AMD has been absent from the X86 server market for so long that many of us have gotten into the habit of only speaking about the Xeon server space and how it relates to the relatively modest (in terms of market share, not in terms of architecture and capability) competition that Intel has faced in the past eight years.

Those days are over now that AMD has successfully got its first X86 server chip out the door with the launch of the “Naples” chip, the first in a line of processors that will carry the Epyc brand and, if all

Competition Returns To X86 Servers In Epyc Fashion was written by Timothy Prickett Morgan at The Next Platform.

AMD Winds Up One-Two Compute Punch For Servers

While AMD voluntarily exited the server processor arena in the wake of Intel’s onslaught with the “Nehalem” Xeon processors during the Great Recession, it never stopped innovating with its graphics processors and it kept enough of a hand in smaller processors used in consumer and selected embedded devices to start making money again in PCs and to take the game console business away from IBM’s Power chip division.

Now, after five long years of investing, AMD is poised to get its act together and to storm the glass house with a new line of server processors based on its Zen

AMD Winds Up One-Two Compute Punch For Servers was written by Timothy Prickett Morgan at The Next Platform.

Cray CTO On The Cambrian Compute Explosion

What goes around comes around. After fighting so hard to drive volume economics in the HPC arena with relatively inexpensive X86 clusters in the past twenty years, those economies of scale are running out of gas. That is why we are seeing an explosion in the diversity of compute, not just on the processor, but in adjunct computing elements that make a processor look smarter than it really is.

The desire of system architects to try everything because it is fun has to be counterbalanced by a desire to make systems that can be manufactured at a price that is

Cray CTO On The Cambrian Compute Explosion was written by Timothy Prickett Morgan at The Next Platform.

Knights Landing Can Stand Alone—But Often Won’t

It is a time of interesting architectural shifts in the world of supercomputing but one would be hard-pressed to prove that using the mid-year list of the top 500 HPC systems in the world. We are still very much in an X86 dominated world with the relatively stable number of accelerated systems to spice the numbers, but there are big changes afoot—as we described in depth when the rankings were released this morning.

This year, the list began to lose one of its designees in the list of “accelerator/offload” architectures as the Xeon Phi moves from offload model to host

Knights Landing Can Stand Alone—But Often Won’t was written by Nicole Hemsoth at The Next Platform.

HPC Poised For Big Changes, Top To Bottom

There is a lot of change coming down the pike in the high performance computing arena, but it has not happened as yet and that is reflected in the current Top 500 rankings of supercomputers in the world. But the June 2017 list gives us a glimpse into the future, which we think will be as diverse and contentious from an architectural standpoint as in the past.

No one architecture is winning and taking all, and many different architectures are getting a piece of the budget action. This means HPC is a healthy and vibrant ecosystem and not, like enterprise

HPC Poised For Big Changes, Top To Bottom was written by Timothy Prickett Morgan at The Next Platform.

Is HPE’s “Machine” the Novel Architecture to Fit Exascale Bill?

The exascale effort in the U.S. got a fresh injection with R&D funding set to course through six HPC vendors to develop scalable, reliable, and efficient architectures and components for new systems in the post-2020 timeframe.

However, this investment, coming rather late in the game for machines that need hit sustained exaflop performance in a 20-30 megawatt envelope in less than five years, raises a few questions about potential shifts in what the Department of Energy (DoE) is looking for in next-generation architectures. From changes in the exascale timeline and new focal points on “novel architectures” to solve exascale challenges,

Is HPE’s “Machine” the Novel Architecture to Fit Exascale Bill? was written by Nicole Hemsoth at The Next Platform.

Tackling Computational Fluid Dynamics in the Cloud

Cloud computing isn’t just for running office productivity software or realising your startup idea. It can support high-performance computing (HPC) applications that crunch through large amounts of data to produce actionable results.

Using elastic cloud resources to process data in this way can have a real business impact. What might one of these applications look like, and how could the cloud support it?

Let’s take buildings as an example. London’s ‘Walkie Talkie’ skyscraper has suffered from a bad rap of late. First it gave the term ‘hot wheels’ a whole new meaning, melting cars by inadvertently focusing the sun’s rays

Tackling Computational Fluid Dynamics in the Cloud was written by Nicole Hemsoth at The Next Platform.

The Memory Scalability At The Heart Of The Machine

Much has been made of the ability of The Machine, the system with the novel silicon photonics interconnect and massively scalable shared memory pool being developed by Hewlett Packard Enterprise, to already address more main memory at once across many compute elements than many big iron NUMA servers. With the latest prototype, which was unveiled last month, the company was able to address a whopping 160 TB of DDR4 memory.

This is a considerable feat, but HPE has the ability to significantly expand the memory addressability of the platform, using both standard DRAM memory and as lower cost memories such

The Memory Scalability At The Heart Of The Machine was written by Timothy Prickett Morgan at The Next Platform.

American HPC Vendors Get Government Boost for Exascale R&D

The US Department of Energy – and the hardware vendors it partners with – are set to enliven the exascale effort with nearly a half billion dollars in research, development, and deployment investments.  The push is led by the DoE’s Exascale Computing Project and its extended PathForward program, which was announced today.

The future of exascale computing in the United States has been subjected to several changes—some public, some still in question (although we received a bit more clarification and we will get to in a moment). The timeline for delivering an exascale capability system has also shifted, with most

American HPC Vendors Get Government Boost for Exascale R&D was written by Nicole Hemsoth at The Next Platform.