high performance computing on graphics processing units: hgpu.org

Programming

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Overtaking CPU DBMSes with a GPU in Whole-Query Analytic Processing with Parallelism-Friendly Execution Plan Optimization

Adnan Agbaria, David Minor, Natan Peterfruend, Eyal Rozenberg, Ofer Rosenberg, Roman Talyansky

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 780 Ti

October 12, 2016 by hgpu

Understanding Latency Hiding on GPUs

Vasily Volkov

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Thesis

October 12, 2016 by hgpu

SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs

Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu

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Tags: Algorithms, Computer science, CUDA, Information Retrieval, Latent Dirichlet allocation, Machine learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan X

October 12, 2016 by hgpu

Implementation of Frequency Domain Convolution for the Caffe-Framework

Philipp Harzig

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Tags: Caffe, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, Thesis

October 8, 2016 by hgpu

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

Pilar Cossio, David Rohr, Fabio Baruffa, Markus Rampp, Volker Lindenstruth, Gerhard Hummer

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Tags: Bayesian, Biology, Biomolecules, CUDA, Electron microscopy, Heterogeneous systems, Medicine, Microscopy, MPI, nVidia, nVidia GeForce GTX Titan, OpenMP, Package, Tesla K20, Tomography

October 8, 2016 by hgpu

Rinnegan: Efficient Resource Use in Heterogeneous Architectures

Sankaralingam Panneerselvam, Michael Swift

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 650, nVidia GeForce GTX 670, OpenCL

October 8, 2016 by hgpu

GPU Concurrency Choices in Graph Analytics

Masab Ahmad, Omer Khan

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Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 970, OpenCL

October 8, 2016 by hgpu

A Runtime Controller for OpenCL Applications on Heterogeneous System Architectures

Cristiana Bolchini, Stefano Cherubin, Gianluca C. Durelli, Simone Libutti, Antonio Miele, Marco D. Santambrogio

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Tags: ARM, Computer science, Heterogeneous systems, OpenCL, Operating systems

October 8, 2016 by hgpu

Efficient CSR-Based Sparse Matrix-Vector Multiplication on GPU

Jiaquan Gao, Panpan Qi, Guixia He

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Sparse matrix, Tesla C2050, Tesla K20

October 4, 2016 by hgpu

APL on GPUs: A TAIL from the Past, Scribbled in Futhark

Troels Henriksen, Martin Dybdal, Henrik Urms, Anna Sofie Kiehn, Daniel Gavin, Hjalte Abelskov, Martin Elsman, Cosmin Oancea

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Tags: Compilers, Computer science, nVidia, nVidia GeForce GTX 780 Ti, OpenCL, Package, PyOpenCL, Python, Visualization

October 4, 2016 by hgpu

Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks

Roberto DiCecco, Griffin Lacey, Jasmina Vasiljevic, Paul Chow, Graham Taylor, Shawki Areibi

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Tags: Benchmarking, Caffe, Computer science, Deep learning, FPGA, Machine learning, Neural networks, OpenCL, Package

October 4, 2016 by hgpu

Training a Feedback Loop for Hand Pose Estimation

Markus Oberweger, Paul Wohlhart, Vincent Lepetit

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX 780 Ti, Package, Theano

October 4, 2016 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

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high performance computing on graphics processing units: hgpu.org

Programming

Overtaking CPU DBMSes with a GPU in Whole-Query Analytic Processing with Parallelism-Friendly Execution Plan Optimization

Understanding Latency Hiding on GPUs

SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs

Implementation of Frequency Domain Convolution for the Caffe-Framework

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

Rinnegan: Efficient Resource Use in Heterogeneous Architectures

GPU Concurrency Choices in Graph Analytics

A Runtime Controller for OpenCL Applications on Heterogeneous System Architectures

Efficient CSR-Based Sparse Matrix-Vector Multiplication on GPU

APL on GPUs: A TAIL from the Past, Scribbled in Futhark

Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks

Training a Feedback Loop for Hand Pose Estimation

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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