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ARM And AMD X86 Server Chips Get Mainstream Lift From Microsoft

If you want real competition among vendors who supply stuff to you, then sometimes you have to make it happen by yourself. The hyperscalers and big cloud builders of the world can do that, and increasingly they are taking the initiative and fostering such competition for compute.

With its first generation of Open Cloud Servers, which were conceptualized in 2012, put into production for its Azure public cloud in early 2013, and open sourced through the Open Compute Project in January 2014, Microsoft decided to leverage the power of the open source hardware community to make its own server

ARM And AMD X86 Server Chips Get Mainstream Lift From Microsoft was written by Timothy Prickett Morgan at The Next Platform.

How AMD’s Naples X86 Server Chip Stacks Up To Intel’s Xeons

Ever so slowly, and not so fast as to give competitor Intel too much information about what it is up to, but just fast enough to build interest in the years of engineering smarts that has gone into its forthcoming “Naples” X86 server processor, AMD is lifting the veil on the product that will bring it back into the datacenter and that will bring direct competition to the Xeon platform that dominates modern computing infrastructure.

It has been a bit of a rolling thunder revelation of information about the Zen core used in the “Naples” server chip, the brand of

How AMD’s Naples X86 Server Chip Stacks Up To Intel’s Xeons was written by Timothy Prickett Morgan at The Next Platform.

High Times for Low-Precision Hardware

Processor makers are pushing down the precision for a range of new and forthcoming devices, driven by a need that balances accuracy with energy-efficient performance for an emerging set of workloads.

While there will always be plenty of room at the server table for double-precision requirements, especially in high performance computing (HPC). machine learning and deep learning are spurring a fresh take on processor architecture—a fact that will have a trickle-down (or up, depending on how you consider it) effect on the hardware ecosystem in the next few years.

In the last year alone, the emphasis on lowering precision has

High Times for Low-Precision Hardware was written by Nicole Hemsoth at The Next Platform.

The Rise of Flash Native Cache

Burst buffers are growing up—and growing out of the traditional realm of large-scale supercomputers, where they were devised primarily to solve the problems of failure at scale.

As we described in an interview with the creator of the burst buffer concept, Los Alamos National Lab’s Gary Grider, the “simple” problem of checkpointing and restarting a massive system after a crash with a fast caching layer would be more important as system sizes expanded—but the same approach could also extend to application acceleration. As the notion of burst buffers expanded beyond HPC, companies like EMC/NetApp, Cray, and DataDirect Networks (DDN)

The Rise of Flash Native Cache was written by Nicole Hemsoth at The Next Platform.

Naples Opterons Give AMD A Second Chance In Servers

There are not a lot of second chances in the IT racket. AMD wants one, and we think, has earned one.

Such second chances are hard to come by, and we can rattle off a few of them because they are so rare. Intel pivoted from a memory maker to a processor maker in the mid-1980s, and has come to dominate compute in everything but handheld devices. In the mid-1990s, IBM failed to understand the RISC/Unix and X86 server waves swamping the datacenter and nearly went bankrupt and salvaged itself as software and services provider to glass houses. A decade

Naples Opterons Give AMD A Second Chance In Servers was written by Timothy Prickett Morgan at The Next Platform.

Stanford’s TETRIS Clears Blocks for 3D Memory Based Deep Learning

The need for speed to process neural networks is far less a matter of processor capabilities and much more a function of memory bandwidth. As the compute capability rises, so too does the need to keep the chips fed with data—something that often requires going off chip to memory. That not only comes with a performance penalty, but an efficiency hit as well, which explains why so many efforts are being made to either speed that connection to off-chip memory or, more efficiently, doing as much in memory as possible.

The advent of 3D or stacked memory opens new doors,

Stanford’s TETRIS Clears Blocks for 3D Memory Based Deep Learning was written by Nicole Hemsoth at The Next Platform.

Japan to Unveil Pascal GPU-Based AI Supercomputer

A shared appetite for high performance computing hardware and frameworks is pushing both supercomputing and deep learning into the same territory. This has been happening in earnest over the last year, and while most efforts have been confined to software and applications research, some supercomputer centers are spinning out new machines dedicated exclusively to deep learning.

When it comes to such supercomputing sites on the bleeding edge, Japan’s RIKEN Advanced Institute for Computational Science is at the top of the list. The center’s Fujitsu-built K Computer is the seventh fastest machine on the planet according to the Top 500 rankings

Japan to Unveil Pascal GPU-Based AI Supercomputer was written by Nicole Hemsoth at The Next Platform.

CPU, GPU Potential for Visualization and Irregular Code

Conventional wisdom says that choosing between a GPU versus CPU architecture for running scientific visualization workloads or irregular code is easy. GPUs have long been the go-to solution, although recent research shows how the status quo could be shifting.

At SC 16 in Salt Lake City in a talk called CPUs versus GPUs, Dr. Aaron Knoll of the University of Utah, and Professor Hiroshi Nakashima of Kyoto University, presented comparisons of various CPU and GPU-based architectures running visualizations and irregular code. Notably, both researchers have found that Intel Xeon Phi processor-based systems show stand-out performance compared to GPUs for

CPU, GPU Potential for Visualization and Irregular Code was written by Nicole Hemsoth at The Next Platform.

For Big Banks, Regulation is the Mother of GPU Invention

There is something to be said for being at the right place at the right time.

While there were plenty of folks who were in the exact wrong spot when the financial crisis hit in 2007-2008, some technologies were uniquely well timed to meet the unexpected demands of a new era.

In the aftermath of the crash, major investment banks and financial institutions had a tough task ahead to keep up with the wave of regulations instituted to keep them straight. This has some serious procedural impacts, and also came with some heady new demands on compute infrastructure. Post-regulation, investment

For Big Banks, Regulation is the Mother of GPU Invention was written by Nicole Hemsoth at The Next Platform.

Docker Reaches The Enterprise Milestone

In the server virtualization era, there were a couple of virtual machine formats and hypervisors to match them, and despite the desire for a common VM format, the virtual server stacks got siloed into ESXi, KVM, Xen, and Hyper-V stacks with some spicing of PowerVM, Solaris containers and LDOMs, and VM/ESA partitions sprinkled on.

With containers, the consensus has been largely to support the Docker format that was inspired by the foundational Linux container work done by Google, and Docker, the company, was the early and enthusiastic proponent of its way of the Docker way of doing containers.

Now, Docker

Docker Reaches The Enterprise Milestone was written by Timothy Prickett Morgan at The Next Platform.

Microsoft, Stanford Researchers Tweak Cloud Economics Framework

Cloud computing makes a lot of sense for a rapidly growing number of larger enterprises and other organizations, and for any number of reasons. The increased application flexibility and agility engendered by creating a pool of shared infrastructure resources, the scalability and the cost efficiencies, are all key drivers in an era of ever-embiggening data.

With public and hybrid cloud environments, companies can offload the integration, deployment and management of the infrastructure to a third party, taking the pressure off their own IT staffs, and in private and hybrid cloud environments, they can keep their most business-critical data securely behind

Microsoft, Stanford Researchers Tweak Cloud Economics Framework was written by Jeffrey Burt at The Next Platform.

Server Makers Try To Adapt To A Harsher Climate

So, who was the biggest revenue generator, and showing the largest growth in sales, for servers in the final quarter of 2016? Was it Hewlett Packard Enterprise? Was it Dell Technologies? Was it IBM or Cisco Systems or one of the ODMs? Nope. It was the Others category comprised of dozens of vendors that sit outside of the top tier OEMs we know by name and the collective ODMs of the world who some of us know by name.

This is a sign that the server ecosystem is getting more diverse under pressure as the technical and economic climate changes

Server Makers Try To Adapt To A Harsher Climate was written by Timothy Prickett Morgan at The Next Platform.

Solving HPC Conflicts with Containers

It’s an unavoidable truth of information technology that the operators and users are sometimes at odds with each other.

Countless stories, comics, and television shows have driven home two very unpleasant stereotypes: the angry, unhelpful system administrator who can’t wait to say “no!” to a user request, and the clueless, clumsy user always a keystroke away from taking down the entire infrastructure. There is a kernel of truth to them. While both resource providers and resource users may want the same end result — the successful completion of computational tasks — they have conflicting priorities when it comes to achieving

Solving HPC Conflicts with Containers was written by Nicole Hemsoth at The Next Platform.

Looking Down The Long Enterprise Road With Hadoop

Just five years ago, the infrastructure space was awash in stories about the capabilities cooked into the Hadoop platform—something that was, even then, only a few pieces of code cobbled onto the core HDFS distributed storage with MapReduce serving as the processing engine for analytics at scale.

At the center of many of the stories was Cloudera, the startup that took Hadoop to the enterprise with its commercial distribution of the open source framework. As we described in a conversation last year marking the ten-year anniversary of Hadoop with Doug Cutting, one of its creators at Yahoo, the platform

Looking Down The Long Enterprise Road With Hadoop was written by Nicole Hemsoth at The Next Platform.

Bouncing Back To Private Clouds With OpenStack

There is an adage, not quite yet old, suggesting that compute is free but storage is not. Perhaps a more accurate and, as far as public clouds are concerned, apt adaptation of this saying might be that computing and storage are free, and so are inbound networking within a region, but moving data across regions in a public cloud is brutally expensive, and it is even more costly spanning regions.

So much so that, at a certain scale, it makes sense to build your own datacenter and create your own infrastructure hardware and software stack that mimics the salient characteristics

Bouncing Back To Private Clouds With OpenStack was written by Timothy Prickett Morgan at The Next Platform.

Making Remote NVM-Express Flash Look Local And Fast

Large enterprises are embracing NVM-Express flash as the storage technology of choice for their data intensive and often highly unpredictable workloads. NVM-Express devices bring with them high performance – up to 1 million I/O operations per second – and low latency – less than 100 microseconds. And flash storage now has high capacity, too, making it a natural fit for such datacenter applications.

As we have discussed here before, all-flash arrays are quickly becoming mainstream, particularly within larger enterprises, as an alternative to disk drives in environments where tens or hundreds of petabytes of data – rather than the

Making Remote NVM-Express Flash Look Local And Fast was written by Jeffrey Burt at The Next Platform.

AMD Researchers Eye APUs For Exascale

Exascale computing, which has been long talked about, is now – if everything remains on track – only a few years away. Billions of dollars are being spent worldwide to develop systems capable of an exaflops of computation, which is 50 times the performance of the most capacious systems the current Top500 supercomputer rankings and will usher in the next generation of HPC workloads.

As we have talked about at The Next Platform, China is pushing ahead with three projects aimed at delivering exascale systems to the market, with a prototype – dubbed the Tianhe-3 – being prepped for

AMD Researchers Eye APUs For Exascale was written by Jeffrey Burt at The Next Platform.

Mixed Signals From Server Land

With a new generation of Xeon processors coming out later this year from Intel and AMD trying to get back in the game with its own X86 server chips – they probably will not be called Opterons – it is not a surprise to us that server makers are having a bit of trouble making their numbers in recent months. But we are beginning to wonder if something else might be going on here than the usual pause before a big set of processor announcements.

In many ways, server spending is a leading indicator because when companies are willing to

Mixed Signals From Server Land was written by Timothy Prickett Morgan at The Next Platform.

Scaling Compute to Meet Large-Scale CT Scan Demands

Computed tomography (CT) is a widely-used process in medicine and industry. Many X-ray images taken around a common axis of rotation are combined to create a three-dimensional view of an object, including the interior.

In medicine, this technique is commonly used for non-invasive diagnostic applications such as searching for cancerous masses. Industrial applications include examining metal components for stress fractures and comparing produced materials to the original computer-aided design (CAD) specifications. While this process provides invaluable insight, it also presents an analytical challenge.

State-of-the-art CT scanners use synchrotron light, which enables very fine resolution in four dimensions. For example, the

Scaling Compute to Meet Large-Scale CT Scan Demands was written by Nicole Hemsoth at The Next Platform.

Financial Institutions Weigh Risks, Benefits of Cloud Migration

Cloud computing in its various forms is often pitched as a panacea of sorts for organizations that are looking to increase the flexibility of their data and to drive down costs associated with their IT infrastructures. And for many, the benefits are real.

By offloading many of their IT tasks – from processing increasingly large amounts of data to storing all that data – to cloud providers, companies can take the money normally spent in building out and managing their internal IT infrastructures and put it toward other important business efforts. In addition, by having their data in an easily

Financial Institutions Weigh Risks, Benefits of Cloud Migration was written by Jeffrey Burt at The Next Platform.