“I think the most important thing I’d like people to know about SC16 is that it is a great venue for bringing the entire community together, having these conversations about what we’re doing now, what the environment looks like now and what it’ll look like in five, ten fifteen years. The fact that so many people come to this conference allows you to really see a lot of diversity in the technologies being pursued, in the kinds of applications that are being pursued – from both the U.S. environment and also the international environment. I think that’s the most exciting thing that I think about when I think about supercomputing.”
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 Intel Chip Chat, Dr. Figen Ulgen from Intel discusses artificial intelligence workloads that are emerging as a result of greater access to high performance computing. “Noting that “wherever there is computational complexity, HPC can help,” Dr. Ulgen talks about the ways that technologies like voice recognition and natural language processing are growing more sophisticated as compute power increases. Dr. Ulgen additionally highlights Intel’s work with the OpenHPC-based Intel HPC Orchestrator, which promises to be an important step forward in making HPC more accessible to a broader array of customers.”
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.”
“In the long run, if you need orders of magnitude more bandwidth than is currently available there’s a set of technologies that are sometimes referred to as processor in memory – I call it processor at memory – technologies that involves cheaper processors distributed out to adjacent to the memory chips. Processors are cheaper, simpler, lower power. That could allow a significant reduction in cost to build the systems, which allows you to build them a lot bigger and therefore deliver significantly higher memory bandwidth. That’s a very revolutionary change.”
Scientists have taken the closest look yet at molecule-sized machinery called the human preinitiation complex. It basically opens up DNA so that genes can be copied and turned into proteins. The science team formed from Northwestern University, Berkeley National Laboratory, Georgia State University, and UC Berkeley. They used a cutting-edge technique called cryo-electron microscopy and combined it with supercomputer analysis. They published their results May of 2016 in the journal Nature.
The new TOP500 list is out, and Rad is Free HPC is here podcasting the scoop in their own special way. With two new systems in the TOP10, there are many different perspectives to share. “The Cori supercomputer, a Cray XC40 system installed at Berkeley Lab’s National Energy Research Scientific Computing Center (NERSC), slipped into the number 5 slot with a Linpack rating of 14.0 petaflops. Right behind it at number 6 is the new Oakforest-PACS supercomputer, a Fujitsu PRIMERGY CX1640 M1 cluster, which recorded a Linpack mark of 13.6 petaflops.”
In this podcast, Jason Stowe from Cycle Computing provides an update on the world of HPC in the Cloud. After that, he describes how the company is augmenting its software capabilities so that more users can take advantage of HPC for their toughest computing challenges. “Our CycleCloud V6 further optimizes what is already unique about its predecessor, bringing unmatched scalability, provisioning, and data management in a secure process. We are extremely pleased to bring V6 to market.”