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Applicability of GPU Computing for Efficient Merge in In-Memory Databases

Jens Krueger, Martin Grund, Ingo Jaeckel, Alexander Zeier, Hasso Plattner

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Tags: Algorithms, Compression, Computer science, CUDA, Databases, nVidia, Tesla C2050

November 3, 2011 by hgpu

A Comparison of Many-threaded Differential Evolution and Genetic Algorithms on CUDA

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Computer science, CUDA, Differential evolution, Genetic programming, Metaheuristics, nVidia, Task scheduling, Tesla C2050

November 2, 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

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Differential evolution, Heterogeneous systems, nVidia, Optimization, Task scheduling, Tesla C2050

November 1, 2011 by hgpu

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

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

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

Leveraging Binary Translation for Heterogeneous Profiling

Dan Upton, Kim Hazelwood

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Tags: ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C2050

October 30, 2011 by hgpu

CPU and GPU Co-processing for Sound

Aleksander Gjermundsen

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Source codes

Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Filtering, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Package, Signal processing, Tesla C2050, Thesis

October 30, 2011 by hgpu

An Exploration of OpenCL on Multiple Hardware Platforms for a Numerical Relativity Application

Niket K. Choudhary, Sandeep Navada, Rakesh Ginjupalli, Gaurav Khanna

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Tags: Astrophysics, ATI, ATI Radeon HD 5870, Differential equations, nVidia, OpenCL, Partial differential equations, PDEs, Tesla C2050

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

Compiling Stream Applications for Heterogeneous Architectures

Amir H. Hormati

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Tags: Compilers, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Optimization, 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

Applicability of GPU Computing for Efficient Merge in In-Memory Databases

A Comparison of Many-threaded Differential Evolution and Genetic Algorithms on CUDA

Quantum chemical many-body theory on heterogeneous nodes

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

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

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

Efficient Implementation of the eta_T Pairing on GPU

Leveraging Binary Translation for Heterogeneous Profiling

CPU and GPU Co-processing for Sound

An Exploration of OpenCL on Multiple Hardware Platforms for a Numerical Relativity Application

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Compiling Stream Applications for Heterogeneous Architectures

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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