high performance computing on graphics processing units: hgpu.org

hgpu.org » Compilers

A Domain-Specific Approach To Heterogeneous Parallelism

Hassan Chafi, Arvind K. Sujeeth, Kevin J. Brown, HyoukJoong Lee, Anand R. Atreya, Kunle Olukotun

View

Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia GeForce GTX 275

February 27, 2011 by hgpu

A Tuning Framework for Software-Managed Memory Hierarchies

Manman Ren, Ji Young Park, Mike Houston, Alex Aiken, William J. Dally

View

Download (PDF)

Tags: Algorithms, Cell processor, Compilers, Computer science, Optimization, Performance, Playstation, Programming Languages

February 26, 2011 by hgpu

Achieving a single compute device image in OpenCL for multiple GPUs

Jungwon Kim, Honggyu Kim, Joo H. Lee, Jaejin Lee

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, Optimization

February 25, 2011 by hgpu

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

Kanupriya Gulati and Sunil P Khatri

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280

February 21, 2011 by hgpu

Data parallel loop statement extension to CUDA: GpuC

Zeki Bozkus, Rajeev Thakur, William Gropp, Ewing Lusk

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization

February 21, 2011 by hgpu

MCUDA: An Efficient Implementation of CUDA Kernels on Multi-cores

John A. Stratton, Sam S. Stone, and Wen-mei W. Hwu

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, Package

February 20, 2011 by hgpu

Data Layout Transformation Exploiting Memory-Level Parallelism in Structured Grid Many-Core Applications

I-Jui Sung, John A. Stratton, Wen-Mei W. Hwu

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 280

February 20, 2011 by hgpu

Compiler Support for High-level GPU Programming

Tianyi David Han and Tarek S. Abdelrahman

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, Package

February 19, 2011 by hgpu

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Pei-Hung Lin, Jagan Jayaraj, and Paul R. Woodward

View

Download (PDF)

Tags: Cell processor, Code generation, Compilers, Computer science, CUDA, Fortran, High-level Languages, Memory model, nVidia, Tesla C1060

February 17, 2011 by hgpu

GpuC: Data parallel language extension to CUDA

Zeki Bozkus

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization

February 16, 2011 by hgpu

Automatically Generating Efficient Simulation Codes on GPUs from Partial Differential Equations

K.A. Hawick and D.P. Playne

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Finite difference, nVidia, Partial differential equations, PDEs

February 14, 2011 by hgpu

Copperhead: Compiling an embedded data parallel language

Bryan Catanzaro, Michael Garland and Kurt Keutzer

View

Download (PDF)

Source codes

Tags: Code generation, Compilers, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 480, Package

February 13, 2011 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

Hardware-Aware FP4 FlashAttention-4

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

A Domain-Specific Approach To Heterogeneous Parallelism

A Tuning Framework for Software-Managed Memory Hierarchies

Achieving a single compute device image in OpenCL for multiple GPUs

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

Data parallel loop statement extension to CUDA: GpuC

MCUDA: An Efficient Implementation of CUDA Kernels on Multi-cores

Data Layout Transformation Exploiting Memory-Level Parallelism in Structured Grid Many-Core Applications

Compiler Support for High-level GPU Programming

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

GpuC: Data parallel language extension to CUDA

Automatically Generating Efficient Simulation Codes on GPUs from Partial Differential Equations

Copperhead: Compiling an embedded data parallel language

Recent source codes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

EinsummableV3 - graph-based computation with tensor operations support

Most viewed papers (last 30 days)