# cuda-debugging

Walks the agent through CUDA debugging: cuda-gdb, Compute Sanitizer, GPU core dumps, error codes 700 and 702. Useful when a kernel crashes or returns wrong values.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 301 installs · ★ 267
- Author: mohitmishra786
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/mohitmishra786/low-level-dev-skills/tree/HEAD/skills/gpu/cuda-debugging/SKILL.md
- Updated: 2026-06-27
- HTML: https://affpapa.org/en/nevibecode/skills/cuda-debugging

## What it does

The skill lays out a debugging order for CUDA programs. Debug builds use `nvcc -G -g -O0`; sanitizers are fine with `-lineinfo -g -O2`. Skip `-G` and cuda-gdb will not stop inside your kernel — that is the first thing people hit.

Automated checks come next. `compute-sanitizer --tool memcheck` catches out-of-bounds access and leaks, `racecheck` finds races in shared and global memory, `initcheck` flags uninitialized reads, `synccheck` catches missing `__syncthreads`. For interactive work there is cuda-gdb: `info cuda kernels`, `cuda thread (0,0,0)`, stepping through kernel code. Device-side `printf` gets its own section, with notes on buffer size and calling `cudaDeviceSynchronize()` before reading output.

A table covers error codes: 700 `cudaErrorIllegalAddress`, 701 `cudaErrorLaunchOutOfResources`, 702 `cudaErrorLaunchTimeout`, 719 `cudaErrorLaunchFailure`. There is also core dump analysis via `CUDA_ENABLE_COREDUMP_ON_EXCEPTION` and a decision tree for crashes versus wrong results. The last part covers `CUDA_VISIBLE_DEVICES` and MIG.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add mohitmishra786/low-level-dev-skills --skill cuda-debugging -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/cuda-debugging/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/cuda-debugging/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add mohitmishra786/low-level-dev-skills --skill cuda-debugging -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/cuda-debugging/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add mohitmishra786/low-level-dev-skills --skill cuda-debugging -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/cuda-debugging/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install mohitmishra786/low-level-dev-skills cuda-debugging
```

2. **Manually: put the files in place**
- File: `.github/skills/cuda-debugging/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add mohitmishra786/low-level-dev-skills --skill cuda-debugging -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/mohitmishra786/low-level-dev-skills --path skills/gpu/cuda-debugging
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/cuda-debugging/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add mohitmishra786/low-level-dev-skills --skill cuda-debugging -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/mohitmishra786/low-level-dev-skills/tree/HEAD/skills/gpu/cuda-debugging/SKILL.md

## When to use it
- track down an out-of-bounds global memory write
- figure out error 700 or 702 after a launch
- find a race between warps in shared memory
- step through kernel code line by line in cuda-gdb
- read a GPU core dump after a crash

## Example prompts
- Build with `-G -g -O0` and run `compute-sanitizer --tool memcheck`, show me where the out-of-bounds write is
- My kernel crashes with error 700, help me debug it in cuda-gdb
- Run `racecheck` and `synccheck` on this kernel and explain the report

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 53a59f30f89d0725.

BEGIN THIRD-PARTY FILE 53a59f30f89d0725
````text
---
name: cuda-debugging
description: CUDA debugging skill for GPU program correctness. Use when debugging with cuda-gdb, running NVIDIA Compute Sanitizer memcheck/racecheck, analyzing GPU core dumps, or interpreting CUDA error codes 700/702. Activates on queries about cuda-gdb, compute-sanitizer, illegal memory access, launch timeout, or device printf.
---

# CUDA Debugging

## Purpose

Guide agents through debugging CUDA programs with cuda-gdb for interactive GPU thread inspection, NVIDIA Compute Sanitizer for automated memory and race detection, GPU core dump analysis, device-side `printf`, and triaging common CUDA runtime error codes.

## When to Use

- `cudaErrorIllegalAddress` (700) or segmentation fault on device
- Intermittent correctness failures in multi-threaded GPU code
- Debugging race conditions between warps or between host and device
- Stepping through kernel code line-by-line with cuda-gdb
- Validating uninitialized memory reads with initcheck
- Kernel hang or `cudaErrorLaunchTimeout` (702)

## Workflow

### 1. Build for debugging

```bash
# Debug build — disables optimizations, enables device debug
nvcc -G -g -O0 -arch=sm_80 -o app_debug main.cu

# Sanitizer-friendly build (lineinfo helps reports)
nvcc -lineinfo -g -O2 -arch=sm_80 -o app_san main.cu
```

`-G` is required for cuda-gdb source-level stepping. Sanitizers work with optimized builds but `-G` gives clearer line numbers.

### 2. Compute Sanitizer — automated checks

```bash
# Memory errors (OOB, misaligned, leak)
compute-sanitizer --tool memcheck ./app_san

# Shared memory and global memory races
compute-sanitizer --tool racecheck ./app_san

# Uninitialized memory reads
compute-sanitizer --tool initcheck ./app_san

# Synchronization errors (missing __syncthreads)
compute-sanitizer --tool synccheck ./app_san

# Verbose with source correlation
compute-sanitizer --tool memcheck --show-reachable=yes --log-file san.log ./app_san
```

Typical memcheck output:

```
======== Invalid __global__ write of size 4
========     at 0x1a0 in vector_add(vector_add.cu:12)
========     by thread (0,0,0) in block (0,0,0)
======== Address 0x7f... is out of bounds
```

### 3. cuda-gdb interactive session

```bash
# Launch under cuda-gdb
cuda-gdb ./app_debug

# Or attach to running process
cuda-gdb -p <pid>
```

Essential commands:

```gdb
# Break at kernel entry
(cuda-gdb) break vector_add
(cuda-gdb) run

# Focus on GPU threads
(cuda-gdb) info cuda kernels
(cuda-gdb) cuda kernel 0
````
END THIRD-PARTY FILE 53a59f30f89d0725

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