high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Exploring Portability and Performance of OpenCL FPGA Kernels on Intel HARPv2

Anthony M. Cabrera, Roger D. Chamberlain

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, OpenCL

July 7, 2019 by hgpu

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

Roberto Cavicchioli, Nicola Capodieci, Marco Solieri, Marko Bertogna

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, Package, Vulkan

July 7, 2019 by hgpu

Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps

Chaoyang He, Ming Li

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Tags: 3D Graphics and Realism, Algorithms, OpenGL, Rendering

July 7, 2019 by hgpu

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs

Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang

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Tags: ARM, CNN, Compilers, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia Jetson Nano, OpenCL, Package

July 7, 2019 by hgpu

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

Axel Hübl

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Tags: CUDA, HPC, nVidia, Package, Particle-in-cell methods, Physics, Tesla P100, Thesis

July 4, 2019 by hgpu

WCCV: Improving the Vectorization of IF-statements with Warp-Coherent Conditions

Huihui Sun, Florian Fey, Jie Zhao, Sergei Gorlatch

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Tags: Benchmarking, Code generation, Computer science, LLVM, OpenCL, Package, Performance

June 30, 2019 by hgpu

Automated Generation of OpenCL Programs Based on Algebra-Algorithmic Approach

Anatoliy Doroshenko, Oleksii Beketov, Mykola Bondarenko, Olena Yatsenko

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 840 M, OpenCL

June 30, 2019 by hgpu

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Philippe Tillet, H. T. Kung, David Cox

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Tags: Compilers, Computer science, CUDA, Deep learning, High-level Languages, LLVM, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1070, Package

June 30, 2019 by hgpu

ReSYCLator: Transforming CUDA C++ source code into SYCL

Tobias Stauber, Peter Sommerlad

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, SYCL

June 27, 2019 by hgpu

Mirovia: A Benchmarking Suite for Modern Heterogeneous Computing

Bodun Hu, Christopher J. Rossbach

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, Package, Performance, Tesla P100

June 27, 2019 by hgpu

Data-Parallel Flattening by Expansion

Martin Elsman, Troels Henriksen, Niels Gustav Westphal Serup

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Tags: Code generation, Computer science, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package

June 23, 2019 by hgpu

IA-SpGEMM: An Input-aware Auto-tuning Framework for Parallel Sparse Matrix-Matrix Multiplication

Zhen Xie, Guangming Tan, Weifeng Liu, Ninghui Sun

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Tags: Algorithms, Auto-Tuning, Computer science, CUDA, Deep learning, Matrix multiplication, nVidia, Sparse matrix, Tesla P100

June 23, 2019 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

Programming

Exploring Portability and Performance of OpenCL FPGA Kernels on Intel HARPv2

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

WCCV: Improving the Vectorization of IF-statements with Warp-Coherent Conditions

Automated Generation of OpenCL Programs Based on Algebra-Algorithmic Approach

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

ReSYCLator: Transforming CUDA C++ source code into SYCL

Mirovia: A Benchmarking Suite for Modern Heterogeneous Computing

Data-Parallel Flattening by Expansion

IA-SpGEMM: An Input-aware Auto-tuning Framework for Parallel Sparse Matrix-Matrix Multiplication

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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