high performance computing on graphics processing units: hgpu.org

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DOPA: GPU-based protein alignment using database and memory access optimizations

Laiq Hasan, Marijn Kentie, Zaid Al-Ars

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Tags: Algorithms, Bioinformatics, Biology, Computational Complexity, CUDA, Databases, nVidia, nVidia GeForce GTX 275, Optimization, Package, Sequence alignment, Smith-Waterman algorithm

October 21, 2011 by hgpu

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

Peter Zinterhof

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Tags: Algorithms, Computational Complexity, Computer science, Nearest neighbour, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, OpenCL, OpenMPI, Search, Tesla C2050

October 10, 2011 by hgpu

Energy-optimized mapping of application to smartphone platform – A case study of mobile face recognition

Yi-Chu Wang, Kwang-Ting (Tim) Cheng

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Tags: Algorithms, Computational Complexity, Computer science, Computer vision, DSP, Heterogeneous systems, Image recognition, nVidia, Optimization

September 1, 2011 by hgpu

A novel FPGA-based SVM classifier

Markos Papadonikolakis, Christos-Savvas Bouganis

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Tags: Computational Complexity, Computer science, FPGA, Heterogeneous systems

August 15, 2011 by hgpu

A real-time 1080p 2D-to-3D video conversion system

Sung-Fang Tsai, Chao-Chung Cheng, Chung-Te Li, Liang-Gee Chen

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Tags: Algorithms, Computational Complexity, Computer science, nVidia, Rendering, Stereo vision

August 3, 2011 by hgpu

Experiences with hybrid clusters

Eric Van Hensbergen, Damir Jamsek

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Tags: Cell processor, Computational Complexity, Computer science, CUDA, Hybrid computing, MPI, nVidia, Presentation, Tesla

July 27, 2011 by hgpu

Deterministic Sample Sort For GPUs

Frank Dehne, Hamidreza Zaboli

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Tags: Algorithms, Computational Complexity, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285, Sorting

November 12, 2010 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

DOPA: GPU-based protein alignment using database and memory access optimizations

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

Energy-optimized mapping of application to smartphone platform – A case study of mobile face recognition

A novel FPGA-based SVM classifier

A real-time 1080p 2D-to-3D video conversion system

Experiences with hybrid clusters

Deterministic Sample Sort For 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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