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GKLEE: Concolic Verification and Test Generation for GPUs

Guodong Li, Peng Li, Geof Sawaya, Ganesh Gopalakrishnan, Indradeep Ghosh, Sreeranga P. Rajan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Programming techniques

January 12, 2012 by hgpu

Incomplete-LU and Cholesky Preconditioned Iterative Methods Using CUSPARSE and CUBLAS

Maxim Naumov

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, nVidia, Tesla C2050

January 12, 2012 by hgpu

Optimization of power consumption in the iterative solution of sparse linear systems on graphics processors

Hartwig Anzt, Maribel Castillo, Juan C. Fernandez, Vincent Heuveline, Francisco D. Igual, Rafael Mayo and Enrique S. Quintana-Orti

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Mixed precision, nVidia, Tesla C1060

January 11, 2012 by hgpu

A parallel Genetic Programming algorithm for classification

Alberto Cano, Amelia Zafra, Sebastian Ventura

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 480

January 11, 2012 by hgpu

Analysis and optimization of power consumption in the iterative solution of sparse linear systems on multi-core and many-core platforms

Hartwig Anzt, Vincent Heuveline, Jose I. Aliaga, Maribel Castillo, Juan C. Fernandez, Rafael Mayo, Enrique S. Quintana-Orti

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, nVidia, Optimization, Sparse linear iterative solvers, Tesla C1060

January 11, 2012 by hgpu

Exponential integrators on graphic processing units

Lukas Einkemmer

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9800 GTX, Tesla C1060, Thesis

January 11, 2012 by hgpu

Efficient Ray Tracing of Dynamic Scenes on the GPU

Asger Dam Hoedt

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Tags: 3D Graphics and Realism, Computer science, CUDA, KD-tree, nVidia, nVidia GeForce GTX 330 M, Raytracing, Thesis

January 11, 2012 by hgpu

Implementing Genetic Algorithms to CUDA Environment Using Data Parallelization

Masashi Oiso, Yoshiyuki Matsumura, Toshiyuki Yasuda, Kazuhiro Ohkura

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 280

January 11, 2012 by hgpu

Parallel LDPC decoding using CUDA and OpenMP

Joo-Yul Park, Ki-Seok Chung

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Parity-check codes

January 11, 2012 by hgpu

Efficient Model-based 3D Tracking of Hand Articulations using Kinect

Iason Oikonomidis, Nikolaos Kyriazis, Antonis A. Argyros

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 580

January 11, 2012 by hgpu

Massively Parallel GPU Computing of Continuum Robotic Dynamics

Roberto Orellana

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Thesis

January 11, 2012 by hgpu

A Nearest Neighbor Data Structure for Graphics Hardware

Lawrence Cayton

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Databases, Nearest neighbour, nVidia, Tesla C2050

January 11, 2012 by hgpu

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

GKLEE: Concolic Verification and Test Generation for GPUs

Incomplete-LU and Cholesky Preconditioned Iterative Methods Using CUSPARSE and CUBLAS

Optimization of power consumption in the iterative solution of sparse linear systems on graphics processors

A parallel Genetic Programming algorithm for classification

Analysis and optimization of power consumption in the iterative solution of sparse linear systems on multi-core and many-core platforms

Exponential integrators on graphic processing units

Efficient Ray Tracing of Dynamic Scenes on the GPU

Implementing Genetic Algorithms to CUDA Environment Using Data Parallelization

Parallel LDPC decoding using CUDA and OpenMP

Efficient Model-based 3D Tracking of Hand Articulations using Kinect

Massively Parallel GPU Computing of Continuum Robotic Dynamics

A Nearest Neighbor Data Structure for Graphics Hardware

Recent source codes

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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