high performance computing on graphics processing units: hgpu.org

hgpu.org » Benchmarking

Quantifying NUMA and contention effects in multi-GPU systems

Kyle Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla M2070

September 23, 2011 by hgpu

Reducing branch divergence in GPU programs

Tianyi David Han, Tarek S. Abdelrahman

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Programming Languages

September 22, 2011 by hgpu

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

Ashwin Prasad, Jayvant Anantpur, R. Govindarajan

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Tags: Benchmarking, Clustering, Computer science, CUDA, Data parallelism, Flow analysis, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, Optimization

September 20, 2011 by hgpu

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

Wing-kei S. Yu, Ruirui Huang, Sarah Q. Xu, Sung-En Wang, Edwin Kan, G. Edward Suh

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Tags: Benchmarking, Computer science, Memory, nVidia, Performance

September 20, 2011 by hgpu

CuMAPz: a tool to analyze memory access patterns in CUDA

Yooseong Kim, Aviral Shrivastava

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory, nVidia, Performance, Tesla C1060

September 20, 2011 by hgpu

Stream computing on graphics hardware

Ian Buck

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Tags: Algorithms, ATI, ATI Radeon X800 XT, Benchmarking, Brook, Compilers, Computer science, nVidia, nVidia GeForce 6800, Review, Thesis

September 19, 2011 by hgpu

Fast Mersenne prime testing on the GPU

Andrew Thall

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Tags: Algorithms, Benchmarking, CUDA, Mathematical Software, Mathematics, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla C2050

September 15, 2011 by hgpu

Task superscalar: using processors as functional units

Yoav Etsion, Alex Ramirez, Rosa M. Badia, Eduard Ayguade, Jesus Labarta, Mateo Valero

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Tags: Benchmarking, Cell processor, Computer science, Performance, Programming techniques

September 12, 2011 by hgpu

Task Superscalar: An Out-of-Order Task Pipeline

Yoav Etsion, Felipe Cabarcas, Alejandro Rico, Alex Ramirez, Rosa M. Badia, Eduard Ayguade, Jesus Labarta, Mateo Valero

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Tags: Benchmarking, Cell processor, Computer science, Performance, Programming techniques

September 11, 2011 by hgpu

TimeGraph: GPU scheduling for real-time multi-tasking environments

Shinpei Kato, Karthik Lakshmanan, Ragunathan Rajkumar, Yutaka Ishikawa

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Source codes

Tags: Benchmarking, Computer science, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenGL, Operating systems, Package, Real-time graphics, Task scheduling

September 11, 2011 by hgpu

Software-based branch predication for AMD GPUs

Ryan Taylor, Xiaoming Li

Tags: ATI, Benchmarking, Computer science, Performance, Programming techniques

September 11, 2011 by hgpu

Enabling multiple accelerator acceleration for Java/OpenMP

Ronald Veldema, Thorsten Blass, Michael Philippsen

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Tags: Benchmarking, Computer science, CUDA, Java, nVidia, OpenCL, OpenMP, OpenMPI, Tesla M1060

September 9, 2011 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Quantifying NUMA and contention effects in multi-GPU systems

Reducing branch divergence in GPU programs

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

CuMAPz: a tool to analyze memory access patterns in CUDA

Stream computing on graphics hardware

Fast Mersenne prime testing on the GPU

Task superscalar: using processors as functional units

Task Superscalar: An Out-of-Order Task Pipeline

TimeGraph: GPU scheduling for real-time multi-tasking environments

Software-based branch predication for AMD GPUs

Enabling multiple accelerator acceleration for Java/OpenMP

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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