In this podcast, the Radio Free HPC team honors the Festivus tradition of the annual Airing of Grievances. Our random gripes include: the need for a better HPC benchmark suite, the missed opportunity for ARM servers, the skittish battery in the new Macbook Pro, and a lack of an industry standards body for cloud computing.
In this special guest feature, Daniel Gutierrez from insideBIGDATA offers up his 2017 roundup industry predictions from Big Data thought leaders. “AI, ML, and NLP innovations have really exploded this past year but despite a lot of hype, most of the tangible applications are still based on specialized AI and not general AI. We will continue to see new use-cases of such specialized AI across verticals and key business processes. These use-cases would primarily be focused on the evolutionary process improvement side of the digital transformation.”
In this video from the Nvidia Booth at SC16, Jonathan Symonds from MapD presents: How GPUs are Remaking Cloud Computing. “This video discusses how price/performance characteristics of GPUs are changing the nature of cloud computing. The talk includes performance benchmarks on Google Cloud, Amazon Web Services and IBM Softlayer as well as a live demonstration.”
The New 2016 Compendium of Engineering Cloud Case Studies is an invaluable resource for engineers, scientists, managers and executives who believe in the strategic importance of Technical Computing as a Service, in the Cloud, for their organization. It is a collection of 18 selected real-life case studies written by the participants of the UberCloud HPC Experiment. Among these case studies you will find scenarios that resonate with your own situation. You will benefit from the candid descriptions of problems encountered, problems solved, and lessons learned.
In this podcast, the Radio Free HPC team looks at how Shahin Khan fared with his OrionX 2016 Technology Issues and Predictions. “Here at OrionX.net, we are fortunate to work with tech leaders across several industries and geographies, serving markets in Mobile, Social, Cloud, and Big Data (including Analytics, Cognitive Computing, IoT, Machine Learning, Semantic Web, etc.), and focused on pretty much every part of the “stack”, from chips to apps and everything in between. Doing this for several years has given us a privileged perspective. We spent some time to discuss what we are seeing and to capture some of the trends in this blog.”
In this special guest feature, Kim McMahon shares her perspectives on SC16. ““Faster” is the game in HPC. You can achieve speed with GPUs, FPGAs, or faster CPUs. GPUs have been around a while – you go to NVIDIA and that’s where your GPUs are. FPGAs have also been around a while, but recent market actions are now making them a more viable option: Intel’s acquisition of Altera, the maturation of the OpenCL toolchain, Microsoft’s adoption and use of Bing in their data center, AWS adding FPGAs to their cloud offerings.”
In this podcast, the Radio Free HPC team looks at the future of Operating Systems in the new world of computing. In a world that seems to be moving to the cloud and microservices, what will happen to the monolithic OS we have come to know and love?
In this Nvidia podcast, Bryan Catanzaro from Baidu describes how machines with Deep Learning capabilities are now better at recognizing objects in images than humans. “AI gets better and better until it kind of disappears into the background,” says Catanzaro — NVIDIA’s head of applied deep learning research — in conversation with host Michael Copeland on this week’s edition of the new AI Podcast. “Once you stop noticing that it’s there because it works so well — that’s when it’s really landed.”
In this podcast, the Radio Free HPC team reviews the results from SC16 Student Cluster Competition. “This year, the advent of clusters with the new Nvidia Tesla P100 GPUs made a huge impact, nearly tripling the Linpack record for the competition. For the first-time ever, the team that won top honors also won the award for achieving highest performance for the Linpack benchmark application. The team “SwanGeese” is from the University of Science and Technology of China. In traditional Chinese culture, the rare Swan Goose stands for teamwork, perseverance and bravery.”
Accelerated computing continues to gain momentum as the HPC community moves towards Exascale. Our recent Tesla P100 GPU review shows how these accelerators are opening up new worlds of performance vs. traditional CPU-based systems and even vs. NVIDIA’s previous K80 GPU product. We’ve got benchmarks, case studies, and more in the insideHPC Research Report on GPU Accelerators.