• Unifying Massive Data at Cloud Scale

    June 9, 2017

    Enterprises continue to struggle with the issue of data: how to process and move the massive amounts that are coming in from multiple sources, how to analyze the different types of data to best leverage its capabilities, and how to store and unify it across various environments, including on-premises infrastructure and cloud environments. A broad array of major storage players, such as Dell EMC, NetApp and IBM are building out their offerings to create platforms that can do a lot of those things.

    MapR Technologies, which made its bones with its commercial Hadoop distribution, is moving in a similar direction. …

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  • One Hyperscaler Gets The Jump On Skylake, Everyone Else Sidelined

    June 7, 2017

    Well, it could have been a lot worse. About 5.6 percent worse, if you do the math.

    As we here at The Next Platform have been anticipating for quite some time, with so many stars aligning here in 2017 and a slew of server processor and GPU coprocessor announcements and deliveries expected starting in the summer and rolling into the fall, there is indeed a slowdown in the server market and one that savvy customers might be able to take advantage of. But we thought those on the bleeding edge of performance were going to wait to see what Intel, …

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  • When No One Can Make Money In Systems

    June 6, 2017

    Making money in the information technology market has always been a challenge, but it keeps getting increasingly difficult as the tumultuous change in how companies consume compute, storage, and networking rips through all aspects of this $3 trillion market.

    It is tough to know exactly what do to, and we see companies chasing the hot new things, doing acquisitions to bolster their positions, and selling off legacy businesses to generate the cash to do the deals and to keep Wall Street at bay. Companies like IBM, Dell, HPE, and Lenovo have sold things off and bought other things to try …

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  • HPE Looks Ahead To Composable Infrastructure, Persistent Memory

    June 6, 2017

    Over the past several years, the server market has been roiled by the rise of cloud computing that run the applications created by companies and by services offered by hyperscalers that augment or replace such applications. This is a tougher and lumpier market, to be sure.

    The top tier cloud providers like Amazon, Microsoft, and Google not only have become key drivers in server sales but also have turned to original design manufacturers (ODMs) from Taiwan and China for lower cost systems to help populate their massive datacenters. Overall, global server shipments have slowed, and top-tier OEMs are working to …

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  • A Health Check For Code And Infrastructure In The Cloud

    May 24, 2017

    As businesses continue their migration to the cloud, the issue of monitoring the performance and health of their applications gets more challenging as they try to track them across both on-premises environments and in both private and public clouds. At the same time, as they become more cloud-based, they have to keep an eye on the entire stack, from the customer-facing applications to the underlying infrastructure they run on.

    Since its founding eight years ago, New Relic has steadily built upon its first product, a cloud-based application performance management (APM) tool that is designed to assess how well the …

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  • Under The Hood Of Google’s TPU2 Machine Learning Clusters

    May 22, 2017 Paul Teich

    As we previously reported, Google unveiled its second-generation TensorFlow Processing Unit (TPU2) at Google I/O last week. Google calls this new generation “Google Cloud TPUs”, but provided very little information about the TPU2 chip and the systems that use it other than to provide a few colorful photos. Pictures do say more than words, so in this article we will dig into the photos and provide our thoughts based the pictures and on the few bits of detail Google did provide.

    To start with, it is unlikely that Google will sell TPU-based chips, boards, or servers – TPU2 …

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  • Singularity is the Hinge To Swing HPC Cloud Adoption

    May 18, 2017

    For almost a decade now, the cloud has been pitched as a cost-effective way to bring supercomputing out of the queue and into public IaaS or HPC on-demand environments. While there are certainly many use cases to prove that tightly-coupled problems can still work in the cloud despite latency hits (among other issues), application portability is one sticking point.

    For instance, let’s say you have developed a financial modeling application on an HPC on demand service to prove that the model works so you can make the case for purchasing a large cluster to run it at scale on-prem. This …

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  • First In-Depth Look at Google’s New Second-Generation TPU

    May 17, 2017

    It was only just last month that we spoke with Google distinguished hardware engineer, Norman Jouppi, in depth about the tensor processing unit used internally at the search giant to accelerate deep learning inference, but that device—that first TPU—is already appearing rather out of fashion.

    This morning at the Google’s I/O event, the company stole Nvidia’s recent Volta GPU thunder by releasing details about its second-generation tensor processing unit (TPU), which will manage both training and inference in a rather staggering 180 teraflops system board, complete with custom network to lash several together into “TPU pods” that can deliver Top …

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  • The Embiggening Bite That GPUs Take Out Of Datacenter Compute

    May 16, 2017

    We are still chewing through all of the announcements and talk at the GPU Technology Conference that Nvidia hosted in its San Jose stomping grounds last week, and as such we are thinking about the much bigger role that graphics processors are playing in datacenter compute – a realm that has seen five decades of dominance by central processors of one form or another.

    That is how CPUs got their name, after all. And perhaps this is a good time to remind everyone that systems used to be a collection of different kinds of compute, and that is why the …

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  • Cray Supercomputing as a Service Becomes a Reality

    May 16, 2017

    For a mature company that kickstarted supercomputing as we know it, Cray has done a rather impressive job of reinventing itself over the years.

    From its original vector machines, to HPC clusters with proprietary interconnects and custom software stacks, to graph analytics appliances engineered in-house, and now to machine learning, the company tends not to let trends in computing slip by without a new machine.

    However, all of this engineering and tuning comes at a cost—something that, arguably, has kept Cray at bay when it comes to reaching the new markets that sprung up in the “big data” days of …

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