hgpu.org » Approximate computing and storage
Stefano Cherubin, Giovanni Agosta
Tags: Approximate computing and storage, Computer science, CUDA, HPC, Mixed precision, nVidia, OpenCL, Precision, survey
May 3, 2020 by hgpu
Sparsh Mittal
January 14, 2016 by sparsh0mittal
Recent source codes
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Most viewed papers (last 30 days)
- Architecture-Aware LLM Inference Optimization on AMD Instinct GPUs: A Comprehensive Benchmark and Deployment Study
- AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search
- LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs
- An Efficient Heterogeneous Co-Design for Fine-Tuning on a Single GPU
- DRTriton: Large-Scale Synthetic Data Reinforcement Learning for Triton Kernel Generation
- MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?
- CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe
- KernelFoundry: Hardware-aware evolutionary GPU kernel optimization
- Mixed-precision numerics in scientific applications: survey and perspectives
- Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context
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