high performance computing on graphics processing units: hgpu.org

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Exploring Fine-Grained Task-based Execution on Multi-GPU Systems

Long Chen, Oreste Villa, Guang R. Gao

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Tags: Computer science, CUDA, GPU cluster, Molecular dynamics, nVidia, Tesla C1060

November 1, 2011 by hgpu

Quantum chemical many-body theory on heterogeneous nodes

A. Eugene DePrince, Jeff R. Hammond

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Tags: Algorithms, Computational chemistry, CUBLAS, CUDA, Heterogeneous systems, nVidia, Presentation, Tesla C1060, Tesla C2050

November 1, 2011 by hgpu

Rapid Performance of a Generalized Distance Calculation

Scott Fisackerly, Eric Chu, David L. Foster

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla C1060

October 31, 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

Efficient Implementation of the eta_T Pairing on GPU

Yosuke Katoh, Yun-Ju Huang, Chen-Mou Cheng, Tsuyoshi Takagi

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Security, Tesla C1060, Tesla C2050

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

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 by hgpu

Scalability of Incompressible Flow Computations on Multi-GPU Clusters Using Dual-Level and Tri-Level Parallelism

Dana A. Jacobsen, Inanc Senocak

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Tags: CUDA, Fluid dynamics, GPU cluster, MPI, nVidia, OpenMP, Tesla C1060, Tesla S1070

October 25, 2011 by hgpu

Accelerating molecular docking and binding site mapping using FPGAs and GPUs

Bharat Sukhwani

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Tags: Algorithms, Biology, Biomechanics, CUDA, FPGA, Molecular modeling, nVidia, Tesla C1060, Thesis

October 22, 2011 by hgpu

Computational Fluid Dynamics Using Graphics Processing Units: Challenges and Opportunities

S. Pratap Vanka, Aaron F. Shinn, Kirti C. Sahu

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, Review, Tesla C1060

October 21, 2011 by hgpu

Accelerating exotic option pricing and model calibration using GPUs

Andre Bernemann, Ralph Schreyer, Klaus Spanderen

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Tags: CUDA, Finance, GPU cluster, Monte Carlo simulation, nVidia, Tesla C1060

October 21, 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

Exploring Fine-Grained Task-based Execution on Multi-GPU Systems

Quantum chemical many-body theory on heterogeneous nodes

Rapid Performance of a Generalized Distance Calculation

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

Efficient Implementation of the eta_T Pairing on GPU

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

Matrix inversion speed up with CUDA

Scalability of Incompressible Flow Computations on Multi-GPU Clusters Using Dual-Level and Tri-Level Parallelism

Accelerating molecular docking and binding site mapping using FPGAs and GPUs

Computational Fluid Dynamics Using Graphics Processing Units: Challenges and Opportunities

Accelerating exotic option pricing and model calibration 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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