“The drive toward exascale computing, a renewed emphasis on data-centric processing, energy efficiency concerns, and the limitations of memory and I/O performance are all working to reshape High Performance Computing platforms. Many-core accelerators, flash storage, 3D memory, integrated networking, and optical interconnects are just some of the technologies propelling these future architectures. In concert with those developments, the HPC vendor landscape has been churning in response to broader market forces, and these events are going to drive some interesting changes in the coming year.”
“The use of GPUs to accelerate applications is mainstream nowadays, but their adoption in cur- rent clusters presents several drawbacks. In this talk we present the last developments of the rCUDA remote GPU virtualization framework, which is the only one supporting the most recent CUDA version, in addition to leverage the InfiniBand fabric for the sake of performance.”
In this episode, the Radio Free HPC team wraps up the GPU Technology Conference. The theme of the show this year was Deep Learning, a topic that is heating up the market for GPUs with challenges like image recognition and self-driving cars. As a sister conference, the OpenPOWER Summit this week in San Jose showcased the first OpenPower hardware, including a prototype HPC server from IBM that will pave the way to the two IBM/Nvidia/Mellanox Coral supercomputers expected in 2017.
In this video, Tesla does a field test of a software update that will bring powerful auto-steering functionality to its Model S fleet.
“Deep Learning has transformed many important tasks, including speech and image recognition. Deep Learning systems scale well by absorbing huge amounts of data to create accurate models. The computational resources afforded by GPUs have been instrumental to this scaling. However, as Deep Learning has become more mainstream, it has generated some hype, and has been linked to everything from world peace to evil killer robots. In this talk, Dr. Ng will help separate hype from reality, and discuss potential ways that Deep Learning technologies can benefit society in the short and long term.”
Today Quanta Cloud Technology (QCT) announced plans to build the first x86 CPU-based servers with Nvidia’s NVLink high-speed GPU interconnect technology. “NVLink unlocks the full potential of GPU accelerators by enabling CPUs and GPUs to transfer data at unprecedented speeds,” said Sumit Gupta, general manager of the Accelerated Computing business at NVIDIA. “QCT extends the benefits of NVLink to the x86 ecosystem and gives our customers an easy path to higher levels of enterprise and HPC application performance.”
This week insideHPC will be streaming live keynotes from the GPU Technology Conference in San Jose. Today’s keynote will feature Google Senior Fellow Jeff Dean. “Google has built large-scale computer systems for training neural networks, and then applied these systems to a wide variety of problems that have traditionally been very difficult for computers.”