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Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

Anjiang Wei, Allen Nie, Thiago S. F. X. Teixeira, Rohan Yadav, Wonchan Lee, Ke Wang, Alex Aiken

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Tags: Code generation, Computer science, DSL, LLM, Matrix multiplication, nVidia, Optimization, Tesla P100

November 17, 2024 by hgpu

A domain-specific language for geospatial computations on the GPU

Louise Tidestav

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Tags: Computer science, CUDA, DSL, nVidia, nVidia Quadro P 2000, Thesis

October 13, 2024 by hgpu

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

Ruixin Wang, Minghai Lu, Cody Hao Yu, Yi-Hsiang Lai, Tianyi Zhang

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Tags: Computer science, CUDA, Deep learning, DSL, nVidia, Package, Performance, PyTorch, Tesla T4

May 12, 2024 by hgpu

Code Generation for a Variety of Accelerators for a Graph DSL

Ashwina Kumar, M. Venkata Krishna, Prasanna Bartakke, Rahul Kumar, Rajesh Pandian M, Nibedita Behera, Rupesh Nasre

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Tags: Code generation, Computer science, CUDA, DSL, nVidia, nVidia GeForce RTX 2080 Ti, OpenACC, OpenCL, Package, SYCL, Tesla V100

January 14, 2024 by hgpu

A Domain-Extensible Compiler with Controllable Automation of Optimisations

Thomas Kœhler

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Tags: Code generation, Computer science, DSL, Heterogeneous systems, Image processing, Machine learning, OpenCL, Package, Thesis

January 8, 2023 by hgpu

Analysis of High Level implementations for Recursive Methods on GPUs

Cheng Cao, Justin Kalloor

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Tags: Computer science, CUDA, DSL, nVidia, nVidia GeForce RTX 3080, OpenGL, Vulkan

January 9, 2022 by hgpu

GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity

Wei Niu, Zhengang Li, Xiaolong Ma, Peiyan Dong, Gang Zhou, Xuehai Qian, Xue Lin, Yanzhi Wang, Bin Ren

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Tags: Artificial intelligence, Code generation, Computer science, Deep learning, DSL, Neural networks, nVidia, nVidia Titan RTX, OpenCL

August 29, 2021 by hgpu

A Compiler Infrastructure for Accelerator Generators

Rachit Nigam, Samuel Thomas, Zhijing Li, Adrian Sampson

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Tags: Compilers, Computer science, DSL, Hardware Architecture, HLS, Package, Programming Languages

March 14, 2021 by hgpu

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Biagio Cosenza, Nikita Popov, Ben Juurlink, Paul Richmond, Mozhgan Kabiri Chimeh, Carmine Spagnuolo, Gennaro Cordasco, Vittorio Scarano

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Tags: Compilers, Computer science, CUDA, DSL, nVidia, nVidia GeForce GTX Titan XP, Package

January 24, 2021 by hgpu

From Constraint Programming to Heterogeneous Parallelism

Philip Ginsbach

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Tags: AMD Radeon R7, ATI, Code generation, Computer science, DSL, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, OpenCL, OpenMP, Thesis

May 10, 2020 by hgpu

Large-Scale Data Computing Performance Comparisons on SYCL Heterogeneous Parallel Processing Layer Implementations

Woosuk Shin, Kwan-Hee Yoo, Nakhoon Baek

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Tags: Computer science, CUDA, DSL, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, OpenCL, SYCL

March 29, 2020 by hgpu

A Language for Describing Optimization Strategies

Bastian Hagedorn, Johannes Lenfers, Thomas Koehler, Sergei Gorlatch, Michel Steuwer

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Tags: Computer science, DSL, High-level Languages, OpenCL, Package, Scala

February 9, 2020 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

A domain-specific language for geospatial computations on the GPU

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

Code Generation for a Variety of Accelerators for a Graph DSL

A Domain-Extensible Compiler with Controllable Automation of Optimisations

Analysis of High Level implementations for Recursive Methods on GPUs

GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity

A Compiler Infrastructure for Accelerator Generators

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

From Constraint Programming to Heterogeneous Parallelism

Large-Scale Data Computing Performance Comparisons on SYCL Heterogeneous Parallel Processing Layer Implementations

A Language for Describing Optimization Strategies

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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