I’m on my way home from a series of Springtime HPC conferences with boatload of new videos and interviews on the latest in high performance computing. Here are some notable items that may have not made it to the front page.
“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.
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.”
In this video from the University of Houston CACDS HPC Workshop, Jeff Larkin from Nvidia presents: The Past, Present, and Future of OpenACC. “OpenACC is an open specification for programming accelerators with compiler directives. It aims to provide a simple path for accelerating existing applications for a wide range of devices in a performance portable way. This talk with discuss the history and goals of OpenACC, how it is being used today, and what challenges it will address in the future.”
“Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. At the 2015 GPU Technology Conference, you can join the experts who are making groundbreaking improvements in a variety of deep learning applications, including image classification, video analytics, speech recognition, and natural language processing.”