“In my humble opinion, I think that debuggers and profiling tools are far too infrequently used. And it’s not because they’re not there. It’s because people just either don’t know about them, don’t do training on them, or don’t know how to use them. We’re in a state where we have less cycles than we’ve ever had per request, right? So being able to take full advantage of those cycles by having optimized code and optimized run patterns is crucial. Otherwise, you’re just not going to be able to get your work done and the science won’t get done.”
The adoption of computer aided engineering (CAE) powered by high performance computing (HPC) is one of key factors fueling the re-birth of manufacturing. SGI offers an HPC environment that is ideal for CAE solutions. This article is part of 5 article series on how HPC is helping to fuel the growth in manufacturing.
In this video from SC14, Mark O’Conner from Allinea demonstrates the company’s new Forge software development suite. “A shared, intuitive user interface between the debugger and profiler with a single, shallow learning curve ensures scientific developers and HPC experts alike get the maximum value from your tools investment.”
“I will summarize the benefits, challenges, and lessons learned in deploying Titan and in preparing applications to move from conventional CPU architectures to a hybrid, accelerated architectures. I will emphasize on the challenges we have encountered with emerging programming models and how we are addressing these challenges using directive based-approaches. I also plan to discuss the early science outcomes from Titan in diverse areas such as materials sciences, nuclear energy, and engineering sciences. I will also discuss research outcomes from a growing number of industrial partnerships.”
In this Chip Chat podcast, Mike Bernhardt, the Community Evangelist for HPC and Technical Computing at Intel, discusses the importance of code modernization as we move into multi- and many-core systems. Markets as diverse as oil and gas, financial services, and health and life sciences can see a dramatic performance improvement in their code through parallelization.