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Dynamic Task Parallelism with a GPU Work-Stealing Runtime System

Sanjay Chatterjee, Max Grossman, Alina Sbirlea, Vivek Sarkar

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Tags: Computer science, CUDA, Data parallelism, nVidia, Task scheduling, Tesla C2050

November 29, 2011 by hgpu

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Yongpeng Zhang, Frank Mueller

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Data parallelism, GPU cluster, nVidia, Tesla C2050

November 15, 2011 by hgpu

Generation of planar radiographs from 3D anatomical models using the GPU

Andre dos Santos Cardoso

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Tags: Algorithms, Benchmarking, CUDA, Data parallelism, Image processing, Image registration, Medicine, nVidia, nVidia GeForce GT 240, Optimization, Thesis

November 10, 2011 by hgpu

Automatic CUDA Code Synthesis Framework for Multicore CPU and GPU architectures

Hanwoong Jung, Youngmin Yi, Soonhoi Ha

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Tags: Code generation, Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Tesla M2050

October 30, 2011 by hgpu

Computer Finite-Difference Time-Domain Simulation of Electromagnetic Wave Propagation using GPUs

Anna Bonet Manchado

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Tags: Algorithms, CUDA, Data parallelism, Electrodynamics, FDTD, Finite-difference time-domain, Maxwell's equations, nVidia, nVidia GeForce GTX 280, Tesla C2050, Thesis, Visualization

October 23, 2011 by hgpu

An Efficient Stream Buffer Mechanism for Dataflow Execution on Heterogeneous Platforms with GPUs

Ana Balevic, Bart Kienhuis

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Programming techniques, Tesla C2050

October 19, 2011 by hgpu

Bit-Packed Damaged Lattice Potts Model Simulations with CUDA and GPUs

Ken A. Hawick, Mitchell G.B. Johnson

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Tags: CUDA, Data parallelism, Ising model, Materials Science, Nearest neighbour, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Phase transition, Physics, Probability, Tesla C2050, Tesla C2070

October 16, 2011 by hgpu

Anti-parallel Patterns in Fine-grain Data-parallel Programs

Jan Cornelis

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Tags: Benchmarking, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce 8500 GT, nVidia GeForce GTX 280, Performance, Thesis

October 10, 2011 by hgpu

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Aleksandar Ilic, Leonel Sousa

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Tags: Computer science, CUDA, Data parallelism, FFT, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

October 2, 2011 by hgpu

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

Ashwin Prasad, Jayvant Anantpur, R. Govindarajan

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Tags: Benchmarking, Clustering, Computer science, CUDA, Data parallelism, Flow analysis, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, Optimization

September 20, 2011 by hgpu

A data parallel view on polyhedral process networks

Ana Balevic, Bart Kienhuis

Tags: Computer science, Data parallelism, Heterogeneous systems

September 11, 2011 by hgpu

Reliability modeling of MEMS devices on CUDA based HPC setup

Rohit Pathak, Satyadhar Joshi

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Tags: Computer science, CUDA, Data parallelism, nVidia, Performance

August 31, 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

Dynamic Task Parallelism with a GPU Work-Stealing Runtime System

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Generation of planar radiographs from 3D anatomical models using the GPU

Automatic CUDA Code Synthesis Framework for Multicore CPU and GPU architectures

Computer Finite-Difference Time-Domain Simulation of Electromagnetic Wave Propagation using GPUs

An Efficient Stream Buffer Mechanism for Dataflow Execution on Heterogeneous Platforms with GPUs

Bit-Packed Damaged Lattice Potts Model Simulations with CUDA and GPUs

Anti-parallel Patterns in Fine-grain Data-parallel Programs

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

A data parallel view on polyhedral process networks

Reliability modeling of MEMS devices on CUDA based HPC setup

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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