high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce RTX 5080

A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data

Zheng Li, Weiyan Wang, Ruiyuan Li, Chao Chen, Xianlei Long, Linjiang Zheng, Quanqing Xu, Chuanhui Yang

View

Tags: Algorithms, Compression, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce RTX 5080, Package

November 16, 2025 by hgpu

Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks

Aaron Jarmusch, Nathan Graddon, Sunita Chandrasekaran

View

Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, nVidia GeForce RTX 5080, nVidia H100, Performance, PTX

July 20, 2025 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

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

Agentic Code Optimization via Compiler-LLM Cooperation

Agentic Code Optimization via Compiler-LLM Cooperation

See all packages

* * *

* * *

HGPU group © 2010-2026 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: