Knowing how the weather will behave in the near future is indispensable for countless human endeavors. Now, researchers at ECMWF are leveraging the computational power of the Titan supercomputer at Oak Ridge to improve weather forecasting.
Designating the appropriate provider for large MPI applications is critical to taking advantage of all of the compute power available. “A modern HPC system with multiple host cpus and multiple coprocessors such as the Intel Xeon Phi coprocessor housed in numerous racks can be optimized for maximum application performance with intelligent thread placement.”
“The combination of using a host cpu such as an Intel Xeon combined with a dedicated coprocessor such as the Intel Xeon Phi coprocessor has been shown in many cases to improve the performance of an application by significant amounts. When the datasets are large enough, it makes sense to offload as much of the workload as possible. But is this the case when the potential offload data sets are not as large?”
“With the advent of massively parallel computing coprocessors, numerical optimization for deep-learning disciplines is now possible. Complex real-time pattern recognition, for example, that can be used for self driving cars and augmented reality can be developed and high performance achieved with the use of specialized, highly tuned libraries. By just using the Message Passing Interface (MPI) API, very high performance can be attained on hundreds to thousands of Intel Xeon Phi processors.”
In this video from the 2014 Argonne Training Program on Extreme-Scale Computing, Bill Gropp from NCSA presents: Cost of Unintended Synchronization. “At ATPESC 2014, we captured 67 hours of lectures in 86 videos of presentations by pioneers and elites in the HPC community on topics ranging from programming techniques and numerical algorithms best suited for leading-edge HPC systems to trends in HPC architectures and software most likely to provide performance portability through the next decade and beyond.”