Keynote Speaker I: Computing for Big Science: Gravitational Wave Detection
Fengqiu Wang · 2016
Summary form only given. Computing has been playing an important role in the recent LIGO Gravitational Waves (GWs) detection. A graphics processing unit (GPU)-accelerated algorithm developed by Tsinghua University to search for GWs will be introduced. The aim is to facilitate fast detection of GWs with a minimum delay to allow prompt electromagnetic follow-up observations. To maximize the GPU acceleration, an efficient batched parallel computing model significantly reduces the number of synchronizations and optimizes the usage of the memory and hardware resource. The code is tested on the CUDA `Fermi' architecture in a GTX 480 graphics card and its performance is compared with a single core of Intel Core i7 920 (2.67 GHz). A 58-fold speedup is achieved while giving results in close agreement with the CPU implementation. This result indicates that it is possible to conduct a full search for GWs from compact binary coalescence in real time with only one desktop computer equipped with a Fermi GPU card for the initial LIGO detectors which in the past required more than 100 CPUs.