high performance computing on graphics processing units: hgpu.org

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Accelerating Nearest Neighbor Search on Manycore Systems

Lawrence Cayton

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

March 15, 2011 by hgpu

Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining

Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy Sadayappan

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Tags: Computer science, CUDA, Databases, nVidia, Sparse matrix, Tesla C1060

March 15, 2011 by hgpu

Comparing GPU and CPU in OLAP Cubes Creation

Krzysztof Kaczmarski

Tags: Computer science, CUDA, Databases, nVidia, Optimization

March 13, 2011 by hgpu

Relational query coprocessing on graphics processors

Bingsheng He, Mian Lu, Ke Yang, Rui Fang, Naga K. Govindaraju, Qiong Luo, Pedro V. Sander

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce 8800 GTX, Package, Performance

January 19, 2011 by hgpu

Towards Chip-on-Chip Neuroscience: Fast Mining of Frequent Episodes Using Graphics Processors

Yong Cao, Debprakash Patnaik, Sean Ponce, Jeremy Archuleta, Patrick Butler, Wu-chun Feng, Naren Ramakrishnan

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Tags: Computer science, CUDA, Databases, Neuroscience, nVidia, nVidia GeForce GTX 280

December 27, 2010 by hgpu

Frequent itemset mining on graphics processors

Wenbin Fang, Mian Lu, Xiangye Xiao, Bingsheng He, Qiong Luo

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GTX 280

December 21, 2010 by hgpu

Accelerating SQL Database Operations on a GPU with CUDA

Peter Bakkum, Kevin Skadron

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Tags: Computer science, CUDA, Databases, nVidia, Tesla C1060

December 18, 2010 by hgpu

In-memory grid files on graphics processors

Ke Yang, Bingsheng He, Rui Fang, Mian Lu, Naga Govindaraju, Qiong Luo, Pedro Sander, Jiaoying Shi

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce 8800 GTX

December 4, 2010 by hgpu

GPUQP: query co-processing using graphics processors

Rui Fang, Bingsheng He, Mian Lu, Ke Yang, Naga K. Govindaraju, Qiong Luo, Pedro V. Sander

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Review

December 4, 2010 by hgpu

Efficient relational database management using graphics processors

Naga K. Govindaraju, Dinesh Manocha

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Tags: Algorithms, Computer science, Databases, nVidia, nVidia GeForce FX 5900 Ultra, nVidia GeForce FX 6800 Ultra, Sorting

November 30, 2010 by hgpu

Fast computation of database operations using graphics processors

Naga K. Govindaraju, Brandon Lloyd, Wei Wang, Ming Lin, Dinesh Manocha

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Tags: Cg, Computer science, Databases, nVidia, nVidia GeForce FX 5900 Ultra, OpenGL

November 29, 2010 by hgpu

Density-based clustering using graphics processors

Christian Bohm, Robert Noll, Claudia Plant, Bianca Wackersreuther

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GTX 280

November 21, 2010 by hgpu

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BLOCKBENCH: A Framework for Analyzing Private Blockchains

Blockchain Goes Green? Part II: Characterizing the Performance and Cost of Blockchains on the Cloud and at the Edge

hls4ml: Machine learning on FPGAs using HLS

Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

GPJSON: GPU-based JSON data processing system accessible via all GraalVM languages

GPU-based JSON data processing using structural indexes

NEPTUNE: Network- and GPU-aware management of serverless functions at the edge

NEPTUNE: Network- and GPU-aware Management of Serverless Functions at the Edge

HeCBench: a collection of Heterogeneous Computing benchmarks written with CUDA, HIP, SYCL (DPC++), and OpenMP-4.5

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

WARPSPEED: An analytic Data Volume and Performance Estimator for GPU Kernels

Analytical Performance Estimation during Code Generation on Modern GPUs

Celerity HLA: A high-level API on top of Celerity to support functional, C++20 range-adaptors-like patterns

The Celerity High-level API: C++20 for Accelerator Clusters

GPU-Sched

CASE: A Compiler-Assisted SchEduling Framework for Multi-GPU Systems

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating Nearest Neighbor Search on Manycore Systems

Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining

Comparing GPU and CPU in OLAP Cubes Creation

Relational query coprocessing on graphics processors

Towards Chip-on-Chip Neuroscience: Fast Mining of Frequent Episodes Using Graphics Processors

Frequent itemset mining on graphics processors

Accelerating SQL Database Operations on a GPU with CUDA

In-memory grid files on graphics processors

GPUQP: query co-processing using graphics processors

Efficient relational database management using graphics processors

Fast computation of database operations using graphics processors

Density-based clustering using graphics processors

Recent source codes

BLOCKBENCH: A Framework for Analyzing Private Blockchains

hls4ml: Machine learning on FPGAs using HLS

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

GPJSON: GPU-based JSON data processing system accessible via all GraalVM languages

NEPTUNE: Network- and GPU-aware management of serverless functions at the edge

HeCBench: a collection of Heterogeneous Computing benchmarks written with CUDA, HIP, SYCL (DPC++), and OpenMP-4.5

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

WARPSPEED: An analytic Data Volume and Performance Estimator for GPU Kernels

Celerity HLA: A high-level API on top of Celerity to support functional, C++20 range-adaptors-like patterns

GPU-Sched

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