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Iterative GPGPU Linear Solvers for Sparse Matrices

Filip Vesely

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Tags: Brook, Computer science, nVidia, nVidia GeForce 8600 M GS, RapidMind, Sparse linear iterative solvers, Thesis

February 24, 2011 by hgpu

Sparse systems solving on GPUs with GMRES

Raphael Couturier, Stephane Domas

Tags: Computer science, CUBLAS, CUDA, nVidia, Sparse linear iterative solvers, Sparse matrix

February 18, 2011 by hgpu

Parallel Iterative Linear Solvers on GPU: A Financial Engineering Case

Abhijeet Gaikwad, Ioane M. Toke

Tags: Computational finance, CUDA, Finance, nVidia, Sparse linear iterative solvers

November 8, 2010 by hgpu

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

Agentic Code Optimization via Compiler-LLM Cooperation

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

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

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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