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InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU

Heejun Lee, Geon Park, Jaduk Suh, Sung Ju Hwang

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Tags: Computer science, LLM, NLP, nVidia, nVidia GeForce RTX 4090, Package

February 16, 2025 by hgpu

Teaching An Old Dog New Tricks: Porting Legacy Code to Heterogeneous Compute Architectures With Automated Code Translation

Nicolas Nytko, Andrew Reisner, J. David Moulton, Luke N. Olson, Matthew West

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Tags: Code generation, Computer science, CUDA, Fortran, Heterogeneous systems, MPI, nVidia, nVidia A100, OpenCL

February 16, 2025 by hgpu

Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics

Yichao Yuan, Advait Iyer, Lin Ma, Nishil Talati

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Databases, HIP, nVidia, nVidia A40, Package

February 16, 2025 by hgpu

Optimizing the optimizer increasing performance efficiency of modern compilers

Hafsah Shahzad

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Tags: Compilers, Computer science, FPGA, HLS, Intel, nVidia, nVidia GeForce RTX 4070, Thesis

February 10, 2025 by hgpu

Ilargi: a GPU Compatible Factorized ML Model Training Framework

Wenbo Sun, Rihan Hai

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Tags: Computer science, CUDA, Linear Algebra, Machine learning, nVidia, nVidia A40, Package

February 10, 2025 by hgpu

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs

Youhe Jiang, Fangcheng Fu, Xiaozhe Yao, Guoliang He, Xupeng Miao, Ana Klimovic, Bin Cui, Binhang Yuan, Eiko Yoneki

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Tags: Benchmarking, Cloud, Computer science, Heterogeneous systems, LLM, nVidia, nVidia GeForce RTX 4090, nVidia H100, nVidia RTX A6000, Package

February 10, 2025 by hgpu

Towards autonomous resource management: Deep learning prediction of CPU-GPU load balancing

Inigo Gabirondo Lopez

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Tags: AMD Radeon HD 7970, Artificial intelligence, ATI, Computer science, Deep learning, Heterogeneous systems, load balancing, nVidia, nVidia GeForce GTX 970, OpenCL

February 10, 2025 by hgpu

On the Partitioning of GPU Power among Multi-Instances

Tirth Vamja, Kaustabha Ray, Felix George, UmaMaheswari C Devi

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Tags: Computer science, CUDA, Energy-efficient computing, Machine learning, Matrix multiplication, nVidia, nVidia A100, nVidia V100, Performance

February 3, 2025 by hgpu

Fully-Automated Code Generation for Efficient Computation of Sparse Matrix Permanents on GPUs

Deniz Elbek, Kamer Kaya

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia A100, nVidia Quadro GV100, PTX, Sparse matrix

February 3, 2025 by hgpu

CPU-GPU co-execution through the exploitation of hybrid technologies via SYCL

Nozal Raúl, Jose Luis Bosque

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Tags: Computer science, CUDA, Heterogeneous systems, Hybrid computing, LLVM, load balancing, nVidia, nVidia GeForce GT 1030, oneAPI, OpenCL, performance portability, SYCL

February 3, 2025 by hgpu

Profiling Apple Silicon Performance for ML Training

Dahua Feng, Zhiming Xu, Rongxiang Wang, Felix Xiaozhu Lin

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Tags: AI, Apple M2 Max, Apple M2 Pro, Apple M2 Ultra, Computer science, CUDA, Linear Algebra, LLM, Machine learning, nVidia, nVidia GeForce RTX 4090, nVidia GeFroce RTX 2080 Ti, nVidia Quadro RTX 4000, nVidia RTX A6000, Performance, PyTorch

February 3, 2025 by hgpu

Column-Oriented Datalog on the GPU

Yihao Sun, Sidharth Kumar, Thomas Gilray, Kristopher Micinski

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Tags: Computer science, CUDA, Databases, nVidia, nVidia H100, Package

January 27, 2025 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU

Teaching An Old Dog New Tricks: Porting Legacy Code to Heterogeneous Compute Architectures With Automated Code Translation

Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics

Optimizing the optimizer increasing performance efficiency of modern compilers

Ilargi: a GPU Compatible Factorized ML Model Training Framework

Towards autonomous resource management: Deep learning prediction of CPU-GPU load balancing

On the Partitioning of GPU Power among Multi-Instances

Fully-Automated Code Generation for Efficient Computation of Sparse Matrix Permanents on GPUs

CPU-GPU co-execution through the exploitation of hybrid technologies via SYCL

Profiling Apple Silicon Performance for ML Training

Column-Oriented Datalog on the GPU

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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