chisel

TL;DR: Seamless GPU kernel profiling on cloud infrastructure. Write GPU code, run one command, get profiling results. Zero GPU hardware required.

🚀 Recent Releases

• Python Support: Direct profiling of Python GPU applications (PyTorch, TensorFlow, etc.)
• AMD rocprofv3 Support: Full integration with AMD's latest profiling tool

🔮 Upcoming Features

• Web Dashboard: Browser-based visualization of profiling results.
• Multi-GPU Support: Profile the same kernel across multiple GPU types simultaneously.
• Profiling Backend: Use Chisel’s built-in backend to run profiling workloads—no cloud account or API token required.
• More GPU Architectures: Support for most requested GPU type.
• Auto cleaning: Smart cleaning and release of your DigitalOcean resources (destroying the droplet after you don't use it).

💡 Feature Requests

Got a feature idea you'd love to see in Chisel? We'd love to hear from you!

• Open a feature request on GitHub Issues
• Or email us directly at contact [at] herdora [dot] com

Please include a short description of the feature, how you'd use it, and any context that might help us prioritize.

About

Testing and profiling GPU kernels across different hardware is time-consuming and hardware-dependent, as it often involves complex setup, driver compatibility issues, dependency mismatches, and access to specialized GPUs. Chisel removes that friction by letting you run and profile GPU code in the cloud with a single command - no GPU required. It’s the fastest way to validate kernel performance on real NVIDIA and AMD GPUs.

Quick Start

Get up and running in 30 seconds:

# 1. Install chisel
pip install chisel-cli

# 2. Choose your authentication method:
# Option A: Use Chisel's managed authentication (includes $10 free credits)
chisel login

# Option B: Use your own DigitalOcean API token
chisel configure

# 3. Compile your code into an executable
hipcc --amdgpu-target=gfx940 -o examples/simple-mm examples/simple-mm.hip
 # for inlined kernels to python on amd.
nvcc -arch=sm_90 -o examples/my_kernel examples/my_kernel.cu
nvcc -arch=sm_90 -Xcompiler -fPIC -shared -o examples/libvector_add.so examples/vector_add.cu # for inlined kernels to python on nvidia.


# 4. Profile your GPU kernels and applications
chisel profile --rocprofv3="--sys-trace" -f examples/simple-mm "./simple-mm" # since this just copies the file, it isn't placed in a dir on the server.
chisel profile --rocprofv3="--sys-trace" -f examples/hip_vector_add_test.py -f examples/libvector_add_hip.so "python hip_vector_add_test.py"
chisel profile --nsys="--trace=cuda --cuda-memory-usage=true" -f examples/kernel.out "./kernel.out"
chisel profile --nsys="--trace=cuda --cuda-memory-usage=true" -f examples "python examples/simple_gpu_test.py" # syncs the entire examples directory and runs simple_gpu_test.py
# TODO: add the case for when user has "-f examples/"
# TODO: make names in examples/ directory more descriptive.

That's it! 🚀 No GPU hardware needed—develop and profile GPU kernels from any machine. IF USING YOUR OWN DIGITALOCEAN ACCOUNT, ENSURE TO DESTROY DROPLETS VIA THEIR DASHBOARD WHEN DONE.

Getting Started:

• Free Credits: Email contact@herdora.com to get your account with $10 in free credits (no DigitalOcean account needed)
• Bring Your Own Account: Get a DigitalOcean API token here (requires read/write access)

IF USING YOUR OWN DIGITALOCEAN ACCOUNT, ENSURE TO DESTROY DROPLETS VIA THEIR DASHBOARD WHEN DONE.

Commands

Chisel has 4 commands:

chisel login

Authenticate with Chisel's managed backend (includes $10 free credits).

• Email contact@herdora.com to activate an account.

# Login with your Chisel token
chisel login

chisel configure

One-time setup of your DigitalOcean API credentials (for users with their own accounts).

# Interactive configuration
chisel configure

# Non-interactive with token
chisel configure --token YOUR_TOKEN

GPU Support

GPU	Size	Region	Profiling
NVIDIA H100	gpu-h100x1-80gb	NYC2	nsight-compute + nsight-systems
NVIDIA L40S	gpu-l40sx1-48gb	TOR1	nsight-compute + nsight-systems
AMD MI300X	gpu-mi300x1-192gb	ATL1	rocprofv3

Development Setup

# With uv (recommended)
uv sync
uv run chisel <command>

# With pip
pip install -e .

Making updates to PyPI

rm -rf dist/ build/ *.egg-info && python -m build && twine upload dist/*