Jump to content

Connect SuperML | Leeroopedia MCP: Equip your AI agents with best practices, code verification, and debugging knowledge. Powered by Leeroo — building Organizational Superintelligence. Contact us at founders@leeroo.com.

Environment:Sgl project Sglang CUDA

From Leeroopedia


Sgl_project_Sglang_CUDA is the NVIDIA CUDA development toolkit environment for SGLang, providing the compiler, libraries, and headers needed to build and run custom GPU kernels.

Requirements

  • NVIDIA GPU (SM75+ / Turing or newer)
  • CUDA Toolkit 12.3+ (12.8+ for Blackwell SM100/SM120)
  • NVCC compiler and CUDA runtime libraries
  • cuBLAS, cuDNN, cuSPARSE
  • NVIDIA driver 550+
  • `cuda-python` == 12.9
  • `nvidia-cutlass-dsl` >= 4.3.4

Required By

See Also

Page Connections

Double-click a node to navigate. Hold to expand connections.
Principle
Implementation
Heuristic
Environment