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ARCHES: GPU Ray Tracing

ARCHES: GPU Ray Tracing. Motivation – Emergence of Heterogeneous Systems Overview and Approach Uintah Hybrid CPU/GPU Scheduler Current Uintah Infrastructure GPU Abilities Acknowledgements: DoE for funding the CSAFE project from 1997-2012, DOE NETL, DOE NNSA, INCITE

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ARCHES: GPU Ray Tracing

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  1. ARCHES: GPU Ray Tracing Motivation – Emergence of Heterogeneous Systems Overview and Approach Uintah Hybrid CPU/GPU Scheduler Current Uintah Infrastructure GPU Abilities Acknowledgements: DoE for funding the CSAFE project from 1997-2012, DOE NETL, DOE NNSA, INCITE NSF for funding via SDCI and PetaApps Keeneland Computing Facility, supported by NSF under Contract OCI-0910735 Oak Ridge Leadership Computing Facility – DoE Jaguar XK6 System (GPU partition) http://www.uintah.utah.edu

  2. Emergence of Heterogeneous Systems • Motivation - Accelerate Uintah Components: • ARCHES Ray Tracer • Want to utilize all hardware on these systems • Uintah’s asynchronous task-based approach is well suited to take advantage of GPUs Nvidia M2070/90 Tesla GPU + Multi-core CPU Keeneland Initial Delivery System 360 GPUs DoE Titan 1000s of GPUs

  3. Overview and Approach • ARCHES Ray Tracer: • RayTrace task is computationally intensive • Ideal for parallelization on GPU • Offload Ray Tracing and RNG to GPU(s) • Available CPU cores can perform other computation. • Uintah infrastructure now supports GPU task scheduling and execution: • Can access multiple GPUs on-node • Uses Nvidia CUDA C/C++

  4. Random Number Generation • Using NVIDIA cuRANDLibrary • High performance GPU-accelerated random number generation (RNG)

  5. Uintah Hybrid CPU/GPU Scheduler • Create & schedule CPU & GPU tasks • Enables Uintah to “pre-fetch” GPU data • Uintah infrastructure manages: • Queues of CUDA Stream and Event handles • Device memory allocation and transfers • Utilize all available: • CPU cores and GPUs Keenland IDS - HP SL390 Compute Node

  6. Uintah CPU/GPU Scheduler Design

  7. Uintah GPU Scheduler Abilities • Has now run capability jobs on: • Keeneland Initial Delivery System (NICS) • 1440 CPU cores & 360 GPUs simultaneously • Jaguar - GPU partition (OLCF) • 15360 CPU cores & 960 GPUs simultaneously • Shown speedups on fluid-solver code • Nearing Completion of GPU Ray Tracer Prototype • Will run on systems listed above

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