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GPU Declarative Framework

Robert W. Senser, Jr.

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Tags: AMD Radeon R9 270, ATI, Code generation, Computer science, Filtering, Image processing, Matrix inversion, nVidia, OpenCL, Sorting, Tesla S2050, Tesla T20, Thesis

December 1, 2014 by hgpu

A second generation of DEFG: Declarative Framework for GPUs

Robert Senser, Tom Altman

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Tags: Computer science, High-level Languages, nVidia, OpenCL, Tesla T20

July 4, 2014 by hgpu

DEF-G: Declarative Framework for GPU Environment

Robert Senser, Tom Altman

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Tags: Code generation, Computer science, Filtering, nVidia, nVidia GeForce GT 430, OpenCL, Tesla T20

January 5, 2014 by hgpu

Median Based Parallel Steering Kernel Regression for Image Reconstruction

G Dada Khalandhar, V Sai Ram, M Srinivasa Rao, Lalith Srikanth C, Pallav Kumar Baruah, Balasubramanian S, R Raghunatha Sarma

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Tags: Algorithms, CUDA, Image processing, Image reconstruction, nVidia, Tesla T20

August 23, 2013 by hgpu

A Computationally Efficient Parallel Kernel Regression for Image Reconstruction

V.Sairam, M.Srinivasa Rao, G.Dada Khalandhar, L.Srikanth, P.K.Baruah, R.R.Sarma

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Tags: Algorithms, CUDA, Image processing, Image reconstruction, Medicine, nVidia, Tesla T20, Tomography

December 8, 2012 by hgpu

Sparse direct solvers with accelerators over DAG runtimes

Xavier Lacoste, Pierre Ramet, Mathieu Faverge, Yamazaki Ichitaro, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse direct solvers, Tesla T20

May 24, 2012 by hgpu

Cost Efficient PageRank Computation using GPU

Praveen K., Vamshi Krishna K., Anil Sri Harsha B., S. Balasubramanian, P.K. Baruah

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Tags: Algorithms, Computer science, CUBLAS, CUDA, List ranking, nVidia, Sparse matrix, Tesla T20

January 24, 2012 by hgpu

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

A Unified Intermediate Representation and Execution Architecture for Heterogeneous and Distributed Neural Simulation

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelLens: Deploying Triton Kernels to C++ Inference Engines

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

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high performance computing on graphics processing units: hgpu.org

GPU Declarative Framework

A second generation of DEFG: Declarative Framework for GPUs

DEF-G: Declarative Framework for GPU Environment

Median Based Parallel Steering Kernel Regression for Image Reconstruction

A Computationally Efficient Parallel Kernel Regression for Image Reconstruction

Sparse direct solvers with accelerators over DAG runtimes

Recent source codes

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

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

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