Over the course of the last five years, GPU computing has featured prominently in supercomputing as an accelerator on some of the world’s fastest machines. If some supercomputer makers are correct, GPUs will continue to play a major role in high performance computing, but the acceleration they provide will go beyond boosts to numerical simulations. This has been great news for Nvidia’s bottom line since the market for GPU computing is swelling, and for HPC vendors that can integrate those and wrap the proper software stacks around both HPC and machine learning, it could be an equal boon. Deep learning and machine learning was the understated story just six months ago at the International Supercomputing Conference but the framework and application-level connections were not being made between the two, even if the hardware was in place. However, these ties are being proven out at scale as an enhancement to traditional simulations—and HPC hardware vendors, especially those whose bread and butter is in supercomputing, don’t want to be left behind as the world marches past standard HPC operations. Learn more at https://www.nextplatform.com/2016/11/14/crays-new-pascal-xc50-supercomputer-points-richer-hpc-future/