Basic optimization techniques that include an understanding of math functions and how to simplify can go a long way towards better performance. “When optimizing for a parallel SIMD system such as the Intel Xeon Phi coprocessor, it is also important to make sure that the results match the scalar system. Using vector data may cause parts of the computer program to be re-written, so that the compiler can generate vector code.”
At SC15, Intel talked about some transformational high-performance computing technologies and the architecture—Intel® Scalable System Framework (Intel® SSF). Intel describes Intel SSF as “an advanced architectural approach for simplifying the procurement, deployment, and management of HPC systems, while broadening the accessibility of HPC to more industries and workloads.” Intel SSF is designed to eliminate the traditional bottlenecks; the so called power, memory, storage, and I/O walls that system builders and operators have run into over the years.
“With high frequency trading becoming so important, the overall system performance, starting with the acquisition of the data from various markets through to the buy or sell decision relies on low latency between various parts of the system. The feed handlers, which accept the data in various formats, can be multithreaded and take advantage of coprocessors such as the Intel Xeon Phi. The NIC on a system waits for the packets to arrive and can then the information to a specified core on the Intel Xeon Phi coprocessor system for processing.”
“The Amber Molecular Dynamics software is a well known and understood application for the structural dynamics of large biological molecules. With modern computer systems, a speedup in the computations can lead to studying events that occur on longer timescales, as well as statistical convergences. By incorporating the Intel Xeon Phi coprocessor into the workflow on a compute server, additional speedups can be obtained.”
In the pantheon of HPC grand challenges, weather forecasting and long term climate simulation rank right up there with the most complex and computationally demanding problems in astrophysics, aeronautics, fusion power, exotic materials, and earthquake prediction, to name just a few. This special reports looks at how HPC takes on the challenge of global weather forecasting and climate research.
Drug discovery has accelerated with the advent of high performance computing and new algorithms. “A structural bioinformatics algorithm, eFindSuite, can be used to demonstrate how moving the code to a highly parallel implementation can speed up the computation, by using both the Intel Xeon processor and the Intel Xeon Phi coprocessor. eFindSuite is implemented in both Fortran 77 and C++.”
VDI or Virtual Desktop Infrastructure helps companies save money, time and resources. Instead of large bulky machines on every desk in the office, companies can connect multiple workstations to a single computer using thin clients. Instead of replacing individual desktops every year, companies only have to replace thin clients every 5 years. And when it comes time to do updates, the IT staff updates the one computer instead of spending time updating every individual workstation.
The Smith-Waterman algorithm is widely used for pairwise DNA sequence alignment. The computation, consisting of looking for pattern in very long strings of the DNA alphabet, is very demanding. Using the Intel Xeon Phi, tremendous performance gains can be obtained, as long as the algorithms have been modified to take advantage of parallelism.
“Microphysics provides atmospheric heat and moisture tendencies. This module has been optimized to take advantage of the Intel Xeon Phi coprocessor. However, some manual optimization can lead to even greater performance gains. By using manual optimizations, the overall speedup on a host CPU (Intel Xeon E5-2670) was 2.8 X, while the performance of running on the Intel Xeon Phi coprocessor was 3.5 X.”