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Efficient Data Management for GPU Databases

Peter Bakkum, Srimat Chakradhar

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 570, Package

February 21, 2012 by hgpu

Acceleration of Composite Order Bilinear Pairing on Graphics Hardware

Ye Zhang, Chun Jason Xue, Duncan S. Wong, Nikos Mamoulis, S.M. Yiu

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Tags: Algorithms, Cloud, Computer science, CUDA, Elliptic curves, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Security, Tesla M2050

February 21, 2012 by hgpu

GPGPU Processing in CUDA Architecture

Jayshree Ghorpade, Jitendra Parande, Madhura Kulkarni, Amit Bawaskar

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Tags: Computer science, CUDA, Data parallelism, DirectCompute, nVidia, OpenCL, Review

February 21, 2012 by hgpu

Implementation of LTE Mini receiver on GPUs

Jose Vieira

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Tags: Computer science, CUDA, MIMO, nVidia, Thesis

February 20, 2012 by hgpu

Model-Driven Tile Size Selection for DOACROSS Loops on GPUs

Peng Di, Jingling Xue

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques, Tesla C1060

February 20, 2012 by hgpu

A Code Optimization Framework for Performance Portability of GPU Kernels onto Custom Accelerators

Alexandros Papakonstantinou, Deming Chen, Wen-mei Hwu

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Optimization

February 20, 2012 by hgpu

Introducing ‘Bones’: A Parallelizing Source-to-Source Compiler Based on Algorithmic Skeletons

Cedric Nugteren, Henk Corporaal

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL

February 20, 2012 by hgpu

Review: Kd-tree Traversal Algorithms for Ray Tracing

M. Hapala, V. Havran

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Tags: 3D Graphics and Realism, Algorithms, Computer science, KD-tree, nVidia, Raytracing, Review

February 20, 2012 by hgpu

GPU Parallel Statistical and Cube Test Analysis of the SHA-3 Finalist Candidate Hash Functions

Alan Kaminsky

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Tags: Computer science, CUDA, Hashing, nVidia, Package, Security, Tesla C2050

February 18, 2012 by hgpu

Exploiting Segmentation for Robust 3D Object Matching

Michael Krainin, Kurt Konolige, Dieter Fox

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTS 450, OpenGL, Package

February 18, 2012 by hgpu

Performance Portability with the Chapel Language

Albert Sidelnik, Saeed Maleki, Bradford L. Chamberlain, Maria J. Garzaran, David Padua

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 280, Optimization

February 18, 2012 by hgpu

Proposition for propagated occupation grids for non-rigid moving objects tracking

Benjamin Lefaudeux, Gwennael Gate, Fawzi Nashashibi

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

February 17, 2012 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

Efficient Data Management for GPU Databases

GPGPU Processing in CUDA Architecture

Implementation of LTE Mini receiver on GPUs

Model-Driven Tile Size Selection for DOACROSS Loops on GPUs

A Code Optimization Framework for Performance Portability of GPU Kernels onto Custom Accelerators

Introducing ‘Bones’: A Parallelizing Source-to-Source Compiler Based on Algorithmic Skeletons

Review: Kd-tree Traversal Algorithms for Ray Tracing

GPU Parallel Statistical and Cube Test Analysis of the SHA-3 Finalist Candidate Hash Functions

Exploiting Segmentation for Robust 3D Object Matching

Performance Portability with the Chapel Language

Proposition for propagated occupation grids for non-rigid moving objects tracking

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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