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Auto-Tuning CUDA Parameters for Sparse Matrix-Vector Multiplication on GPUs

Ping Guo, Liqiang Wang

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 9500 GTX, nVidia GeForce GTX 295, Sparse matrix

April 21, 2011 by hgpu

Accelerating Linpack Performance with Mixed Precision Algorithm on CPU+GPGPU Heterogeneous Cluster

Wang Lei, Zhang Yunquan, Zhang Xianyi, Liu Fangfang

Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Linear Algebra, Mixed precision, nVidia, nVidia GeForce GTX 295, Tesla C1060

April 20, 2011 by hgpu

CUDA-BLASTP: Accelerating BLASTP on CUDA-Enabled Graphics Hardware

Weiguo Liu, Bertil Schmidt, Wolfgang Muller-Wittig

Source codes

Tags: Bioinformatics, Biology, BLAST, CUDA, nVidia, nVidia GeForce GTX 295, Package, Sequence alignment

April 18, 2011 by hgpu

A distributed multi-GPU system for high speed electron microscopic tomographic reconstruction

Shawn Q. Zheng, Eric Branlund, Bettina Kesthelyi, Michael B. Braunfeld, Yifan Cheng, John W. Sedat, David A. Agard

Tags: CUDA, Image processing, Image reconstruction, nVidia, nVidia GeForce GTX 295, Tomography

April 15, 2011 by hgpu

Scalable instruction set simulator for thousand-core architectures running on GPGPUs

Shivani Raghav, Martino Ruggiero, David Atienza, Christian Pinto, Andrea Marongiu, Luca Benini

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Programming techniques

April 9, 2011 by hgpu

Record Setting Software Implementation of DES Using CUDA

G. Agosta, A. Barenghi, F. De Santis, G. Pelosi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 250, nVidia GeForce GTX 260, nVidia GeForce GTX 275, nVidia GeForce GTX 285, nVidia GeForce GTX 295, Security

April 8, 2011 by hgpu

Enabling Energy-Efficient Analysis of Massive Neural Signals Using GPGPU

Dan Chen, Lizhe Wang, Shuaiting Wang, Muzhou Xiong, Gregor von Laszewski, Xiaoli Li

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Tags: Biology, CUDA, Medicine, Neuroscience, nVidia, nVidia GeForce GTX 295, Signal processing

April 5, 2011 by hgpu

A Case Study of SWIM: Optimization of Memory Intensive Application on GPGPU

Wei Yi, Yuhua Tang, Guibin Wang, Xudong Fang

Tags: Computer science, Memory, nVidia, nVidia GeForce GTX 295, Optimization, Performance

April 4, 2011 by hgpu

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

Andreas Klockner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih

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Tags: Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 9400 M, nVidia GeForce GTX 295, nVidia GeForce GTX 480, OpenCL, Package, PyOpenCL, Python, Software Engineering, Tesla C1060

March 30, 2011 by hgpu

GPU-based password cracking

Marcus Bakker, Roel Van Der Jagt

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Review, Security

March 21, 2011 by hgpu

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs

Mark Van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse

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Tags: Computer science, CUDA, CULA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 295, Tesla C1060

March 20, 2011 by hgpu

Password recovery for encrypted ZIP archives using GPUs

Pham Hong Phong, Phan Duc Dung, Duong Nhat Tan, Nguyen Huu Duc, Nguyen Thanh Thuy

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Tags: Archivers, Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Security

March 19, 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

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high performance computing on graphics processing units: hgpu.org

Auto-Tuning CUDA Parameters for Sparse Matrix-Vector Multiplication on GPUs

Accelerating Linpack Performance with Mixed Precision Algorithm on CPU+GPGPU Heterogeneous Cluster

CUDA-BLASTP: Accelerating BLASTP on CUDA-Enabled Graphics Hardware

A distributed multi-GPU system for high speed electron microscopic tomographic reconstruction

Scalable instruction set simulator for thousand-core architectures running on GPGPUs

Record Setting Software Implementation of DES Using CUDA

Enabling Energy-Efficient Analysis of Massive Neural Signals Using GPGPU

A Case Study of SWIM: Optimization of Memory Intensive Application on GPGPU

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

GPU-based password cracking

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs

Password recovery for encrypted ZIP archives using GPUs

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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