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Benchmarking Next Generation Hardware Platforms: An Experimental Approach

Vishakha Gupta, Adit Ranadive, Ada Gavrilovska, Karsten Schwan

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Tags: Benchmarking, CUDA, Finance, Heterogeneous systems, Image processing, nVidia, nVidia GeForce 8800 GTX

March 1, 2012 by hgpu

Cooperative Heterogeneous Computing for Parallel Processing on CPU/GPU Hybrids

Changmin Lee, Won W. Ro, Jean-Luc Gaudiot

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9400 GT

February 26, 2012 by hgpu

Power-Efficient Time-Sensitive Mapping in Heterogeneous Systems

Cong Liu, Jian Li, Wei Huang, Juan Rubio, Evan Speight, Xiaozhu Lin

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Tags: ATI, ATI Radeon HD 5770, Computer science, Energy-efficient computing, Heterogeneous systems, OpenCL

February 26, 2012 by hgpu

Collision Detection of Triangle Meshes using GPU

Nils Backman

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Tags: Collision detection, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, OpenCL, Thesis

February 24, 2012 by hgpu

Efficient Data Management for GPU Databases

Peter Bakkum, Srimat Chakradhar

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 570, Package

February 21, 2012 by hgpu

A Code Optimization Framework for Performance Portability of GPU Kernels onto Custom Accelerators

Alexandros Papakonstantinou, Deming Chen, Wen-mei Hwu

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Optimization

February 20, 2012 by hgpu

LAMMPScuda – a new GPU accelerated Molecular Dynamics Simulations Package and its Application to Ion-Conducting Glasses

Christian Robert Trott

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Tags: Biology, Computational Physics, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 470, Package, Physics, Polymer Systems, Tesla C1060, Thesis

February 13, 2012 by hgpu

Characterizing and Evaluating a Key-value Store Application on Heterogeneous CPU-GPU Systems

Tayler H. Hetherington, Timothy G. Rogers, Lisa Hsu, Mike O'Connor, Tor M. Aamodt

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6310, ATI Radeon HD 6550, Computer science, Databases, Heterogeneous systems, OpenCL

February 11, 2012 by hgpu

Implementing Molecular Dynamics on Hybrid High Performance Computers – Particle-Particle Particle-Mesh

W. Michael Brown, Axel Kohlmeyer, Steven J. Plimpton, Arnold N. Tharrington

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Tags: Algorithms, Chemistry, CUDA, Electrostatics, GPU cluster, Heterogeneous systems, Molecular dynamics, nVidia, OpenCL, OpenMPI, Package, Physics, Tesla M2070

February 10, 2012 by hgpu

Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units

Jun Igarashi, Osamu Shouno, Tomoki Fukai, Hiroshi Tsujino

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce GTX 280, Visualization

February 9, 2012 by hgpu

Auto-Generation and Auto-Tuning of 3D Stencil Codes on GPU Clusters

Yongpeng Zhang, Frank Mueller

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Nearest neighbour, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Tesla C1060, Tesla C2050

February 8, 2012 by hgpu

The PEPPHER Approach to Programmability and Performance Portability for Heterogeneous many-core Architectures

Siegfried Benkner, Sabri Pllana, Jesper Larsson Traff, Philippas Tsigas, Andrew Richards, Raymond Namyst, Beverly Bachmayer, Christoph Kessler, David Moloney, Peter Sanders

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Performance, Tesla C1060

February 8, 2012 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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