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Join Algorithms on GPUs: A Revisit After Seven Years

Ran Rui, Hao Li, Yi-Cheng Tu

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

October 25, 2015 by hgpu

Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

Jorge Alberto Castro Godinez

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Tags: Computer science, Parallelization, Review, Thesis

October 22, 2015 by hgpu

A linguistic approach to concurrent, distributed, and adaptive programming across heterogeneous platforms

Paul Harvey

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Tags: Computer science, Heterogeneous systems, OpenCL, Thesis

October 22, 2015 by hgpu

Stadium Hashing: Scalable and Flexible Hashing on GPUs

Farzad Khorasani, Mehmet E. Belviranli, Rajiv Gupta, Laxmi N. Bhuyan

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 780

October 22, 2015 by hgpu

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Linnan Wang, Wei Wu, Jianxiong Xiao, Yi Yang

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Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K40

October 22, 2015 by hgpu

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

Lev E. Givon, Aurel A. Lazar

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Source codes

Tags: Biology, Computer science, CUDA, nVidia, OpenMPI, Tesla K20

October 22, 2015 by hgpu

Self-Adapting Parallel Framework for Long-Term Object Tracking

Salim Mohammed Ali

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Tags: AMD Radeon HD 8970 M, ATI, Computer science, Computer vision, nVidia, nVidia GeForce GTX 580, OpenCL, Thesis

October 18, 2015 by hgpu

A Network Intrusion Detection System Framework based on Hadoop and GPGPU

Sanraj Bandre, Jyoti Nandimath

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Tags: Computer science, CUDA, Hadoop, nVidia, Security, Tesla K20

October 18, 2015 by hgpu

MetaFork: A Compilation Framework for Concurrency Models Targeting Hardware Accelerators and Its Application to the Generation of Parametric CUDA Kernels

Changbo Chen, Xiaohui Chen, Abdoul-Kader Keita, Marc Moreno Maza, Ning Xie

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Tags: Code generation, Computer science, CUDA, nVidia, Package

October 18, 2015 by hgpu

Comparison of Thread Execution Methods for GPU-oriented OpenCL Programs on Multicore Processors

Naohisa Hojo, Ittetsu Taniguchi, Hiroyuki Tomiyama

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Tags: Benchmarking, Computer science, OpenCL, Performance

October 16, 2015 by hgpu

A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection

Chun-Liang Lee, Yi-Shan Lin, Yaw-Chung Chen

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Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX 680, Security

October 13, 2015 by hgpu

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

Linchuan Chen

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, Matrix multiplication, MPI, nVidia, Sparse matrix, Task scheduling, Tesla M2070, Thesis

October 13, 2015 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Join Algorithms on GPUs: A Revisit After Seven Years

Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

A linguistic approach to concurrent, distributed, and adaptive programming across heterogeneous platforms

Stadium Hashing: Scalable and Flexible Hashing on GPUs

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

Self-Adapting Parallel Framework for Long-Term Object Tracking

A Network Intrusion Detection System Framework based on Hadoop and GPGPU

MetaFork: A Compilation Framework for Concurrency Models Targeting Hardware Accelerators and Its Application to the Generation of Parametric CUDA Kernels

Comparison of Thread Execution Methods for GPU-oriented OpenCL Programs on Multicore Processors

A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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