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Towards Unified Analysis of GPU Consistency

Haining Tong, Natalia Gavrilenko, Hernán Ponce de León, Keijo Heljanko

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Tags: Computer science, Memory, nVidia, OpenCL, Package, PTX, Vulkan

July 7, 2024 by hgpu

Automatic Code Rewriting for Performance Portability

Alister Johnson

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Tags: Compilers, Computer science, HIP, OpenCL, OpenMP, performance portability, SYCL, Thesis

July 7, 2024 by hgpu

Composing Distributed Computations Through Task and Kernel Fusion

Rohan Yadav, Shiv Sundram, Wonchan Lee, Michael Garland, Michael Bauer, Alex Aiken, Fredrik Kjolstad

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Tags: Computer science, CUDA, Distributed computing, MPI, nVidia, nVidia DGX-A100, Python

June 30, 2024 by hgpu

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Jacob O. Tørring, Carl Hvarfner, Luigi Nardi, Magnus Själander

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Tags: Benchmarking, Compilers, Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan V, nVidia Titan RTX, OpenCL, Package

June 30, 2024 by hgpu

Adapting database components to heterogeneous environments

Dimitrios Koutsoukos

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia P100, Thesis

June 30, 2024 by hgpu

A Survey of General-purpose Polyhedral Compilers

Arun Thangamani, Vincent Loechner, Stéphane Genaud

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia A100, OpenCL, Package, survey

June 30, 2024 by hgpu

Breaking the Memory Wall: A Study of I/O Patterns and GPU Memory Utilization for Hybrid CPU-GPU Offloaded Optimizers

Avinash Maurya, Jie Ye, M. Mustafa Rafique, Franck Cappello, Bogdan Nicolae

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Tags: Computer science, CUDA, LLM, Memory, nVidia, nVidia A100, nVidia H100, Performance

June 23, 2024 by hgpu

An End-to-End Programming Model for AI Engine Architectures

Maksim Levental

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Tags: Artificial intelligence, Computer science, Deep learning, nVidia, nVidia GeForce RTX 3080 Ti, Thesis, Vulkan

June 23, 2024 by hgpu

Optimal Kernel Orchestration for Tensor Programs with Korch

Muyan Hu, Ashwin Venkatram, Shreyashri Biswas, Balamurugan Marimuthu, Bohan Hou, Gabriele Oliaro, Haojie Wang, Liyan Zheng, Xupeng Miao, Jidong Zhai

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Tags: Compilers, Computer science, CUDA, Neural networks, nVidia, nVidia A100, nVidia V100, Package, PyTorch

June 23, 2024 by hgpu

COOK Access Control on an embedded Volta GPU

Benjamin Lesage, Frédéric Boniol, Claire Pagetti

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia Jetson AGX Xavier

June 23, 2024 by hgpu

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Johannes Pekkilä, Oskar Lappi, Fredrik Robertsén, Maarit J. Korpi-Lagg

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, Energy-efficient computing, HIP, nVidia, nVidia A100, nVidia V100, Package, Performance, PyTorch, Stencil computation

June 16, 2024 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

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

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high performance computing on graphics processing units: hgpu.org

Towards Unified Analysis of GPU Consistency

Automatic Code Rewriting for Performance Portability

Composing Distributed Computations Through Task and Kernel Fusion

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Adapting database components to heterogeneous environments

A Survey of General-purpose Polyhedral Compilers

Breaking the Memory Wall: A Study of I/O Patterns and GPU Memory Utilization for Hybrid CPU-GPU Offloaded Optimizers

An End-to-End Programming Model for AI Engine Architectures

Optimal Kernel Orchestration for Tensor Programs with Korch

COOK Access Control on an embedded Volta GPU

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Recent source codes

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Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

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

DuoReduce: MLIR's benchmark

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