Applications are now being accepted for the Women in IT Networking at SC (WINS) program at SC17. The conference takes place Nov. 12-17 in Denver. “The WINS program seeks qualified female U.S. candidates in their early to mid-career to join the SCinet volunteer team to help build and operate SCinet for SC17. Selected candidates will receive full travel support and mentoring by well-known engineering experts in the research and education community.”
Scott Callaghan from the Southern California Earthquake Center presented this talk as part of the Blue Waters Webinar Series. “I will present an overview of scientific workflows. I’ll discuss what the community means by “workflows” and what elements make up a workflow. We’ll talk about common problems that users might be facing, such as automation, job management, data staging, resource provisioning, and provenance tracking, and explain how workflow tools can help address these challenges. I’ll present a brief example from my own work with a series of seismic codes showing how using workflow tools can improve scientific applications.”
The Data Science with Spark Workshop addresses high-level parallelization for data analytics workloads using the Apache Spark framework. Participants will learn how to prototype with Spark and how to exploit large HPC machines like the Piz Daint CSCS flagship system.
In this video, Ricard Borrell from the Barcelona Supercomputing Center describes how the Mont Blanc Project Industrial End User Group on TermoFluids is advancing HPC on ARM-based platforms.
“This video is from the opening session of the “Introduction to Programming Pascal (P100) with CUDA 8″ workshop at CSCS in Lugano, Switzerland. The three-day course is intended to offer an introduction to Pascal computing using CUDA 8.”
“GPUs potentially offer exceptionally high memory bandwidth and performance for a wide range of applications. The challenge in utilizing such accelerators has been the difficulty in programming them. Enter GPU Hackathons; Our mentors come from national laboratories, universities and vendors, and besides having extensive experience in programming GPUs, many of them develop the GPU-capable compilers and help define standards such as OpenACC and OpenMP.”
“Do you need to compress your software development cycles for services deployed at scale and accelerate your data-driven insights? Are you delivering solutions that automate decision making & model complexity using analytics and machine learning on Spark? Find out how a pre-integrated analytics platform that’s tuned for memory-intensive workloads and powered by the industry leading interconnect will empower your data science and software development teams to deliver amazing results for your business. Learn how Cray’s supercomputing approach in an enterprise package can help you excel at scale.”
“Electricity transformed industries: agriculture, transportation, communication, manufacturing. I think we are now in that phase where AI technology has advanced to the point where we see a clear path for it to transform multiple industries.” Specifically, Ng sees AI being particularly influential in entertainment, retail, and logistics.
In this video, Dr. Marcelo Ponce from SciNet presents: Scientific Visualization with Python. “SciNet is Canada’s largest supercomputer centre, providing Canadian researchers with computational resources and expertise necessary to perform their research on scales not previously possible in Canada. We help power work from the biomedical sciences and aerospace engineering to astrophysics and climate science.”
“This talk will describe Monotasks, a new architecture for the core of Spark that makes performance easier to reason about. In Spark today, pervasive parallelism and pipelining make it difficult to answer even simple performance questions like “what is the bottleneck for this workload?” As a result, it’s difficult for developers to know what to optimize, and it’s even more difficult for users to understand what hardware to use and what configuration parameters to set to get the best performance.”