high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce RTX 2070

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Orestis Zachariadis, Nitin Satpute, Juan Gómez-Luna, Joaquín Olivares

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Matrix multiplication, Mixed precision, nVidia, nVidia GeForce RTX 2070, nVidia Titan RTX, Package, Performance, Sparse matrix

October 4, 2020 by hgpu

Hash-Based Authentication Revisited in the Age of High-Performance Computers

Niclas Hedam, Jakob Mollerup, Pinar Tozun

View

Download (PDF)

Tags: Computer science, CUDA, Databases, Hashing, nVidia, nVidia GeForce RTX 2070, OpenCL, Security, Tesla V100

September 6, 2020 by hgpu

Heterogeneous parallel computing for image registration and linear algebra applications

Orestis Zachariadis

View

Download (PDF)

Source codes

Tags: CUDA, Heterogeneous systems, Image processing, Image registration, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 1050, nVidia GeForce RTX 2070, Package, Sparse matrix, Thesis

August 9, 2020 by hgpu

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Grigory Glukhov, Aleksandra Soltan

View

Download (PDF)

Tags: 3D Graphics and Realism, AMD RX Vega 64, ATI, Neural networks, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2070, Thesis, Voxelization, Vulkan

June 23, 2019 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

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Hash-Based Authentication Revisited in the Age of High-Performance Computers

Heterogeneous parallel computing for image registration and linear algebra applications

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

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

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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

Most viewed papers (last 30 days)