high performance computing on graphics processing units: hgpu.org

Phitchaya Mangpo Phothilimthana, Archibald Samuel Elliott, An Wang, Abhinav Jangda, Bastian Hagedorn, Henrik Barthels, Samuel J. Kaufman, Vinod Grover, Emina Torlak, Rastislav Bodik

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro GV100

February 3, 2019 by hgpu

The OoO VLIW JIT Compiler for GPU Inference

Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica

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Tags: Compilers, Computer science, CUDA, Data parallelism, Machine learning, nVidia, Tesla V100

February 3, 2019 by hgpu

High Performance Algorithms for Counting Collisions and Pairwise Interactions

Matheus Henrique Junqueira Saldanha, Paulo Sérgio Lopes de Souza

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Tags: Collision detection, Computer science, CUDA, nVidia, Package, Tesla P100

February 3, 2019 by hgpu

DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression

Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, Franck Cappello

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Tags: Compression, Computer science, Deep learning, Neural networks, nVidia, Performance, Tesla V100

February 3, 2019 by hgpu

Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Emanuele Vitali, Davide Gadioli, Gianluca Palermo, Andrea Beccari, Carlo Cavazzoni, Cristina Silvano

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, molecular docking, MPI, nVidia, OpenACC, OpenMP, Tesla K80

January 27, 2019 by hgpu

Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

Martin Lucke

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX 1080, OpenCL, Partial differential equations, PDEs, performance portability, Thesis

January 27, 2019 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

DeeperLab: Single-Shot Image Parser

GPU Accelerated Keccak (SHA3) Algorithm

Performance Evaluation of OpenMP’s Target Construct on GPUs: Exploring Compiler Optimizations

Heterogeneous Distributed Big Data Clustering on Sparse Grids

Hierarchical Matrix Operations on GPUs: Matrix-Vector Multiplication and Compression

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Swizzle Inventor: Data Movement Synthesis for GPU Kernels

The OoO VLIW JIT Compiler for GPU Inference

High Performance Algorithms for Counting Collisions and Pairwise Interactions

DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression

Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

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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