high performance computing on graphics processing units: hgpu.org

Steven G. Parker, James Bigler, Andreas Dietrich, Heiko Friedrich, Jared Hoberock, David Luebke, David McAllister, Morgan McGuire, Keith Morley, Austin Robison, Martin Stich

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 485, nVidia Quadro FX 5800, PTX, Raytracing, Software Engineering

September 14, 2011 by hgpu

Collision-streams: fast GPU-based collision detection for deformable models

Min Tang, Dinesh Manocha, Jiang Lin, Ruofeng Tong

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL

September 11, 2011 by hgpu

TimeGraph: GPU scheduling for real-time multi-tasking environments

Shinpei Kato, Karthik Lakshmanan, Ragunathan Rajkumar, Yutaka Ishikawa

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Source codes

Tags: Benchmarking, Computer science, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenGL, Operating systems, Package, Real-time graphics, Task scheduling

September 11, 2011 by hgpu

Interactive volumetric lighting simulating scattering and shadowing

Timo Ropinski, Christian Doring, Christof Rezk-Salama

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Tags: 3D Graphics and Realism, Computed tomography, CT, GLSL, Medicine, nVidia, nVidia GeForce GTX 285, OpenGL, Rendering, Tomography, Ultrasound

September 4, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

Flexible, high performance convolutional neural networks for image classification

Parallel probabilistic model checking on general purpose graphics processors

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

GPU Accelerated Computation of the ICON Model

An MDE Approach for Automatic Code Generation from MARTE to OpenCL

Randomized selection on the GPU

Processing data streams with hard real-time constraints on heterogeneous systems

OptiX: a general purpose ray tracing engine

Collision-streams: fast GPU-based collision detection for deformable models

TimeGraph: GPU scheduling for real-time multi-tasking environments

Interactive volumetric lighting simulating scattering and shadowing

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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