high performance computing on graphics processing units: hgpu.org

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CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, PTX, Sequence alignment, Smith-Waterman algorithm

April 10, 2013 by hgpu

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

Jianlong Zhong, Bingsheng He

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, PTX, Task scheduling, Tesla C2050

March 23, 2013 by hgpu

Just-in-time Acceleration of JavaScript

Uday Pitambare, Arun Chauhan, Saurabh Malviya

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Tags: Computer science, Java, nVidia, Performance, PTX, Tesla C1060

March 12, 2013 by hgpu

Software Reliability Enhancements for GPU Applications

Si Li, Naila Farooqui, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 660 Ti, PTX

February 2, 2013 by hgpu

Scaling CUDA for Distributed Heterogeneous Processors

Siu Kwan Lam

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, MPI, nVidia, Package, PTX, Python, Thesis

July 20, 2012 by hgpu

Analyzing the CUDA Applications with its Latency and Bandwidth Tolerance

V.N. Pistulkar, C.A. Uttarwar

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Tags: Computer science, CUDA, GPU cluster, nVidia, PTX, Tesla C1060

July 5, 2012 by hgpu

Parallel Cryptanalysis

Ruben Falko Niederhagen

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 295, PTX, Security, Thesis

May 12, 2012 by hgpu

Usable assembly language for GPUs: a success story

Daniel J. Bernstein, Hsieh-Chung Chen, Chen-Mou Cheng, Tanja Lange, Ruben Niederhagen, Peter Schwabe, Bo-Yin Yang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Performance, PTX, Security

March 18, 2012 by hgpu

An Energy Consumption Model for GPU Computing at Instruction Level

Haifeng Wang, Qingkui Chen

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Tags: Code generation, Computer science, Energy-efficient computing, nVidia, nVidia GeForce GTX 280, PTX

February 27, 2012 by hgpu

Symbolic Testing of OpenCL Code

Peter Collingbourne, Cristian Cadar, Paul H. J. Kelly

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Tags: Benchmarking, Code generation, Computer science, nVidia, OpenCL, Package, PTX, Tesla C1060

February 8, 2012 by hgpu

Solving Discrete Logarithms in Smooth-Order Groups with CUDA

Ryan Henry, Ian Goldberg

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Tags: Algorithms, Computer science, CUDA, nVidia, Package, PTX, Security, Tesla M2050

January 29, 2012 by hgpu

A Compile-Time Managed Multi-Level Register File Hierarchy

Mark Gebhart, Stephen W. Keckler, William J. Dally

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, nVidia, Optimization, PTX

January 19, 2012 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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high performance computing on graphics processing units: hgpu.org

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

Just-in-time Acceleration of JavaScript

Software Reliability Enhancements for GPU Applications

Scaling CUDA for Distributed Heterogeneous Processors

Analyzing the CUDA Applications with its Latency and Bandwidth Tolerance

Parallel Cryptanalysis

Usable assembly language for GPUs: a success story

An Energy Consumption Model for GPU Computing at Instruction Level

Symbolic Testing of OpenCL Code

Solving Discrete Logarithms in Smooth-Order Groups with CUDA

A Compile-Time Managed Multi-Level Register File Hierarchy

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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