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Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation

Alin Murarasu, Josef Weidendorfer, Arndt Bode

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Tags: Compression, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Task scheduling, Tesla C2050

October 31, 2011 by hgpu

Environment Segmentation in Service Robotics

Matthew S. Roscoe, Paul G Ploger

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Tesla S2070

October 31, 2011 by hgpu

High-performance software rasterization on GPUs

Samuli Laine, Tero Karras

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Source codes

Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Rasterization

October 31, 2011 by hgpu

Parallel implematation of flow and matching algorithms

Agnieszka Lupinska

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 560 Ti

October 31, 2011 by hgpu

Automatic CUDA Code Synthesis Framework for Multicore CPU and GPU architectures

Hanwoong Jung, Youngmin Yi, Soonhoi Ha

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Tags: Code generation, Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Tesla M2050

October 30, 2011 by hgpu

Accelerating Real-time processing of the ATST Adaptive Optics System using Coarse-grained Parallel Hardware Architectures

V. Venugopal, K. Richards, S. Barden, T. Rimmele, S. Gregory, L. Johnson

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Tags: Algorithms, Benchmarking, CUDA, DSP, FPGA, nVidia, Optics, Physics, Tesla C1060, Tesla C2050

October 30, 2011 by hgpu

A scalable hybrid algorithm based on domain decomposition and algebraic multigrid for solving partial differential equations on a cluster of CPU/GPUs

Li Luo, Chao Yang, Yubo Zhao, Xiao-Chuan Cai

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FFT, Finite difference, GPU cluster, nVidia, Partial differential equations, PDEs, Tesla C1060

October 30, 2011 by hgpu

Optimizing and Auto-tuning Belief Propagation on the GPU

Scott Grauer-Gray, John Cavazos

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 470, Optimization, Tesla C870

October 30, 2011 by hgpu

Effective Parallelization of Non-bonded Interactions Kernel for Virtual Screening on GPUs

Gines D. Guerrero, Horacio Perez-Sanchez, Wolfgang Wenzel, Jose M. Cecilia, Jose M. Garcia

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Tags: Bioinformatics, Biology, CUDA, nVidia, Optimization, Pharmaceuticals, Tesla C1060

October 30, 2011 by hgpu

Improving Energy Efficiency of GPU based General-Purpose Scientific Computing through Automated Selection of Near Optimal Configurations

Xiaohan Ma, Marion Rincon, Zhigang Deng

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 8800 GT

October 30, 2011 by hgpu

Using GPUs to Accelerate Installed Antenna Performance Simulations

Tod Courtney, John E. Stone, Bob Kipp

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Tags: CUDA, Electrodynamics, nVidia, nVidia GeForce GTX 480, Raytracing

October 29, 2011 by hgpu

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Muhammad Mustafa Rafique

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, Prefetch, Software Engineering, Tesla C2050, Thesis

October 28, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation

Environment Segmentation in Service Robotics

High-performance software rasterization on GPUs

Parallel implematation of flow and matching algorithms

Automatic CUDA Code Synthesis Framework for Multicore CPU and GPU architectures

Accelerating Real-time processing of the ATST Adaptive Optics System using Coarse-grained Parallel Hardware Architectures

A scalable hybrid algorithm based on domain decomposition and algebraic multigrid for solving partial differential equations on a cluster of CPU/GPUs

Optimizing and Auto-tuning Belief Propagation on the GPU

Effective Parallelization of Non-bonded Interactions Kernel for Virtual Screening on GPUs

Improving Energy Efficiency of GPU based General-Purpose Scientific Computing through Automated Selection of Near Optimal Configurations

Using GPUs to Accelerate Installed Antenna Performance Simulations

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

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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