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Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

Guillermo Vigueras, Manuel Carro, Salvador Tamarit, Julio Marino

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Tags: Computer science, Heterogeneous systems, Machine learning, OpenCL, Programming Languages

March 15, 2016 by hgpu

Melia: A MapReduce Framework on OpenCL-based FPGAs

Zeke Wang, Shuhao Zhang, Bingsheng He, Wei Zhang

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Tags: Computer science, FPGA, MapReduce, OpenCL, Package

March 15, 2016 by hgpu

Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs

Wei Tan, Liangliang Cao, Liana Fong

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Factorization, nVidia, nVidia GeForce GTX Titan X, OpenMP, Tesla K80

March 15, 2016 by hgpu

Machine Learning at the Limit

John Canny, Huasha Zhao, Ye Chen, Bobby Jaros, Jiangchang Mao

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan X, Package

March 12, 2016 by hgpu

SGO: An ultrafast engine for atomic structure global optimization by differential evolution

Zhanghui Chen, Lin-Wang Wang

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Tags: Condensed matter, Differential evolution, Materials Science, nVidia, nVidia GeForce GTX 980

March 12, 2016 by hgpu

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

F. Hariri, T.M. Tran, A. Jocksch, E. Lanti, J. Progsch, P. Messmer, S. Brunner, G. Gheller, L. Villard

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Tags: Computational Physics, Heterogeneous systems, nVidia, OpenACC, Particle-in-cell methods, Physics, Plasma physics, Tesla K20

March 12, 2016 by hgpu

Clinically applicable Monte Carlo-based biological dose optimization for the treatment of head and neck cancers with spot-scanning proton therapy

H. Wan Chan Tseung, J. Ma, C. R. Kreofsky, D. Ma, C. Beltran

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Tags: Medical Physics, nVidia, nVidia GeForce GTX Titan X, Physics, Tesla K20

March 12, 2016 by hgpu

Automatic and Explicit Parallelization Approaches for Mathematical Simulation Models

Mahder Gebremedhin

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Tags: Compilers, Computer science, nVidia, OpenCL, Tesla M2050, Thesis

March 12, 2016 by hgpu

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

David S. Lawrie

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Tags: Algorithms, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 780 M, nVidia GeForce GTX 980

March 10, 2016 by hgpu

Automatic Data Layout Generation and Kernel Mapping for CPU+GPU Architectures

Deepak Majeti, Kuldeep S. Meel, Rajkishore Barik, Vivek Sarkar

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Tags: Algorithms, Compilers, Computer science, Heterogeneous systems, nVidia, OpenCL, Programming techniques, Tesla M2050

March 10, 2016 by hgpu

Pragma Directed Shared Memory Centric Optimizations on GPUs

Jing Li, Lei Liu, Yuan Wu, Xiang-Hua Liu, Yi Gao, Xiao-Bing Feng, Cheng-Yong Wu

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Tags: ATI, ATI Radeon HD 7850, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenACC, OpenCL, Tesla C2050

March 10, 2016 by hgpu

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Varun Nagpal

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C1060, Thesis

March 10, 2016 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

Applications

Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code

Melia: A MapReduce Framework on OpenCL-based FPGAs

Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs

Machine Learning at the Limit

SGO: An ultrafast engine for atomic structure global optimization by differential evolution

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

Clinically applicable Monte Carlo-based biological dose optimization for the treatment of head and neck cancers with spot-scanning proton therapy

Automatic and Explicit Parallelization Approaches for Mathematical Simulation Models

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

Automatic Data Layout Generation and Kernel Mapping for CPU+GPU Architectures

Pragma Directed Shared Memory Centric Optimizations on GPUs

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

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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