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  • Momentum for Bioinspired GPU Computing at the Edge

    April 3, 2018

    Bioinspired computing is nothing new but with the rise in mainstream interest in machine learning, these architectures and software frameworks are seeing fresh light. This is prompting a new wave of young companies that are cropping up to provide hardware, software, and management tools—something that has also spurred a new era of thinking about AI problems.

    We most often think of these innovations happening at the server and datacenter level but more algorithmic work is being done (to suit better embedded hardware) to deploy comprehensive models on mobile devices that allow for long-term learning on single instances of object recognition …

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  • What’s Ahead for Supercomputing’s Balanced Benchmark

    March 21, 2018

    We all know about the Top 500 supercomputing benchmark, which measures raw floating point performance. But over the several years there has been talk that this no longer represents real-world application performance.

    This has opened the door for a new benchmark to come to the fore, in this case the high performance conjugate gradients benchmark, or HPCG, benchmark.

    Here to talk about this on today’s episode of “The Interview” with The Next Platform is one of the creators of HPCG, Sandia National Lab’s Dr. Michael Heroux. Interestingly, Heroux co-developed HPCG with one of the founders of the Top …

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  • Using Python to Snake Closer to Simplified Deep Learning

    March 15, 2018

    On today’s episode of “The Interview” with The Next Platform, we discuss the role of higher level interfaces to common machine learning and deep learning frameworks, including Caffe.

    Despite the existence of multiple deep learning frameworks, there is a lack of comprehensible and easy-to-use high-level tools for the design, training, and testing of deep neural networks (DNNs) according to this episode’s guest, Soren Klemm, one of the creators of Python based Barista, which is an open-source graphical high-level interface for the Caffe framework.

    While Caffe is one of the most popular frameworks for training DNNs, editing prototxt files in …

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  • Open Source Data Management for All

    March 14, 2018

    On today’s episode of “The Interview” with The Next Platform, we talk about an open source data management platform (and related standards group) called iRODS, which many in scientific computing already know—but that also has applicability in enterprise.

    We found that several of our readers had heard of iRODS and knew it was associated with a scientific computing base, but few understood what the technology was and were not aware that there was a consortium. To dispel any confusion, we spoke with Jason Coposky, executive director of the iRODS Consortium about both the technology itself and the group’s role …

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  • Networks Within Networks: Optimization at Massive Scale

    March 13, 2018

    On today’s episode of “The Interview” with The Next Platform we talk about the growing problem of networks within networks (within networks) and what that means for future algorithms and systems that will support smart cities, smart grids, and other highly complex and interdependent optimization problems.

    Our guest on this audio interview episode (player below) is Hadi Amini, a researcher at Carnegie Mellon who has focused on the interdependency of many factors for power grids and smart cities in a recent book series on these and related interdependent network topics. Here, as in the podcast, the focus is on the …

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  • Pushing Greater Stream Processing Platform Evolution

    March 8, 2018

    Today’s episode of “The Interview” with The Next Platform is focused on the evolution of stream processing—from the early days to more recent times with vast volumes of social, financial, and other data challenging data analysts and systems designers alike.

    Our guest is Nathan Trueblood, a veteran of several companies like Mirantis, Western Digital, EMC, and current VP of product management at DataTorrent—a company comprised of many ex-Yahoo employees who worked with the Hadoop platform and have pushed the evolution of that framework to include more real-time requirements with Apache Apex.

    Trueblood’s career has roots in high performance computing …

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  • Expanding Use Cases Mean Tape Storage is Here to Stay

    March 7, 2018

    On today’s episode of “The Interview” with The Next Platform we talk about the past, present, and future of tape storage with industry veteran Matt Starr.

    Starr is CTO at tape giant, Spectra Logic and has been with the company for almost twenty-five years. He was the lead engineer and architect forthe design and production of Spectra’s enterprise tape library family, which is still a core product.

    We talk about some of the key evolutions in tape capacity and access speeds over the course of his career before moving into where the new use cases at massive scale are. In …

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  • Machine Learning for Auto-Tuning HPC Systems

    March 6, 2018

    On today’s episode of “The Interview” with The Next Platform we discuss the art and science of tuning high performance systems for maximum performance—something that has traditionally come at high time cost for performance engineering experts.

    While the role of performance engineer will not disappear anytime soon, machine learning is making tuning systems—everything from CPUs to application specific parameters—less of a burden. Despite the highly custom nature of systems and applications, reinforcement learning is allowing new leaps in time-saving tuning as software learns what works best for user applications and architectures, freeing up performance engineers to focus on the finer …

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  • OpenACC Developments: Past, Present, and Future

    March 2, 2018

    On today’s episode of “The Interview” with The Next Platform we talk with Doug Miles who runs the PGI compilers and tools team at Nvidia about the past, present, and future of OpenACC with an emphasis on what lies ahead in the next release.

    Over the last few years we have described momentum with OpenACC in a number of articles covering everything from what it means in the wake of new memory options to how it pushes on OpenMP to develop alongside. Today, however, we take a step back with an HPC code veteran for the bigger picture and …

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  • Geographic Information Systems (GIS) Field Upended by Neural Networks

    February 28, 2018 Nicole Hemsoth

    On today’s episode of “The Interview” with The Next Platform, we focus on how geographic information systems (GIS) is, as a field, being revolutionized by deep learning.

    This stands to reason given the large volumes of satellite image data and robust deep learning frameworks that excel at image classification and analysis–a volume issue that has been compounded by more satellites with ever-higher resolution output.

    Unlike other areas of large-scale scientific data analysis that have traditionally relied on massive supercomputers, our audio interview (player below) reveals that a great deal of GIS analysis can be done on smaller systems. However, …

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