The GPU Computing Revolution - London Mathematical Society

8 THE GPU COMPUTING REVOLUTIONFrom Multi-Core CPUs To Many-Core Graphics Processorswith Prof. Paul Kelly at ImperialCollege, but early results arealready impressive. Using an airfoiltest code with a single-precision 2DEuler equation, a problem with 0.75million cells and 1.5 million edgeshas been solved in 7.4 secondsusing a single NVIDIA C2070 GPU.Double-precision performance wasroughly half this, taking 15.4seconds on the same problem.When OP2 generates similarlyoptimised code for a pair ofcontemporary Intel ‘Westmere’6-core 2.67GHz X5650 CPUs, thesame problem takes 34.2 secondsto solve in single precision and 44.6seconds in double precision. OneGPU has therefore deliveredimpressive relative speedups of4.6X and 2.9X for single and doubleprecision respectively, compared to12 top-of-the-range CPU cores.OP2 is being developed as an opensource project and potential userscan contact Prof. Giles via theproject webpage [44].Other CFD examples — Anothersuccessful project using GPUs forCFD has been Turbostream,developed by Tobias Brandvik andDr Graham Pullan in the WhittleLaboratory at the University ofCambridge [18, 19]. In contrast toOP2’s unstructured grid approach,Turbostream solves theNavier-Stokes equations bydiscretising the problem onto astructured grid and then performingexplicit time-stepping to solve theresulting partial differentialequations (PDEs) using athree-dimensional stencil operation.Turbostream is another example ofan approach that enables theprogrammer to work at a higherlevel of abstraction: rather thanprogrammers having to writecomplex, low-level codethemselves, the programmerspecifies the required stenciloperations in a high-leveldescription from which Turbostreamautomatically generates optimisedcode targeting the latest GPUs andmulti-core CPUs.Turbostream has achievedimpressive performanceimprovements, with speedups inthe range of 10–20X on the latestNVIDIA GPUs compared withoptimised code running on a fastquad-core Intel CPU. AdditionallyTurbostream has shown goodscalability, using up to 64 GPUs atonce. Turbostream is available tolicense and the reader is referred tothe project website for moreinformation [20].Others have also been achievinggreat success in using GPUs toaccelerate CFD problems. BAESystems has announced it is usinga GPU-accelerated cluster todeliver near-interactive speeds fortheir CFD simulations [37]. A teamat Stanford University was recentlysuccessful in modelling hypersonicairflows using a GPU-basedsystem [33].These early successes indicatethat CFD is an application area thatshould see increasing benefit fromGPUs in the future; for additionalinformation see the CFD Onlinewebsite [24].Molecular dockingusing GPUs: BUDEThe University of Bristol has beenat the forefront of moleculardocking for the past decade [41].Molecular docking is the process ofsimulating the interaction betweentwo molecules, where one moleculeis typically a protein of medicalinterest in the human body, and thesecond represents a potential newdrug.The Bristol University DockingEngine (BUDE) was originallydeveloped to run on a commoditycluster of x86-based CPUs, but asearly as 2006 it was ported to oneof the first generation of many-coreprocessors, the CSX architecturefrom ClearSpeed [75]. In 2010Figure 3: GPUs have enabled BAE Systems to investigate the aerodynamic performance of aircraft throughadvanced CFD simulations (source: BAE Systems).