Jet Engine Aerodynamics on GPUs - many-core.group - University of ...

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• OurCFDcodeis:AreGPUsagoodfitforCFD?– SIMD(samefuncAonsappliedtoallcellsindomain)– Singleprecision– Largedatasets(c10Mnodes)fitonone4GBTeslacard• (bandwithoncardishighc100GB/smuchslowerto/fromcardc8GB/sandstepsinCFDare“memorybound”)
Pre‐CUDA–GPUcoercionApplication specifies geometry – GPUrasterizesEach fragment is shaded (SIMD)Shading can use values from memory(textures)Courtesy, John Owens, UC DavisImage can be stored for re-use
Page 1 and 2: NVIDIA ® TESLAJET ENGINE AERODYNAM
Page 3 and 4: TurbomachineryThousands of bladesAr
Page 5 and 6: IntroducAontoCFDBladeFlowDivide the
Page 7 and 8: GoverningequaAonsforeachcellConserv
Page 9 and 10: Example:massconservaAon• Sumfluxe
Page 11 and 12: SimilarityofstepsEach step uses dat
Page 13 and 14: CPUrunAmes(x86machines)Steadyapprox
Page 15 and 16: ThepurposeofGPUs
Page 17: GraphicsandscienAficcompuAngGPUsare
Page 21 and 22: CUDA• GraphicsabstracAonisremoved
Page 23 and 24: • DivideupdomainOverallstrategy-
Page 25 and 26: CUDAexample__global__ void smooth_k
Page 27 and 28: ExampleSBLOCKdefiniAonkind = "stenc
Page 29 and 30: CUDAimplementaAon__global__ void sm
Page 31 and 32: Turbostream• 9minutesonaTeslaS870
Page 33 and 34: ImpactofGPUacceleratedCFD• TeslaP
Page 35: MoreinformaAonwww.many-core.group.c

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