cumm-cu126

library0.8.2pypypi✓ verified 85d ago

cuMM is a high-performance CUDA matrix multiplication library designed for deep learning and scientific computing. It provides optimized GEMM (General Matrix Multiply) kernels and supports various precision formats. Version 0.8.2 requires Python >=3.8 and is actively maintained.

ai-ml data

pip install cumm-cu126

github ↗package ↗

INSTALL

IMPORT

SIG · CUMM-CU126

cumm-cu126

ai-mlpythonv0.8.2

Install

14.0s avg

Import

428ms

Disk

245MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.8.2 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

build_error

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 14.0s · import 0.428s · 231MB

245MB installed

● package 245MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

cumm

✓ import cumm

✗ import cumm-cu126

cumm-cu126 is the package name on PyPI, but the import module is 'cumm'.

cumm.functional

✓ from cumm import functional

✗ from cumm_cu126 import functional

The module name does not include the CUDA version suffix.

Basic GEMM operation using cuMM with PyTorch tensors.

import cumm import torch x = torch.randn(128, 128, device='cuda') y = torch.randn(128, 128, device='cuda') z = cumm.gemm(x, y) print(z.shape)

Debug

Known issues

breakingcuMM requires a compatible CUDA toolkit (CUDA 12.6) and NVIDIA GPU drivers. Running on an unsupported CUDA version may cause import errors or runtime crashes.

fix

Ensure your system has CUDA 12.6 installed and set LD_LIBRARY_PATH appropriately.

affects: all

gotchaThe library name on PyPI is 'cumm-cu126', but the Python module to import is simply 'cumm'. Do not use the PyPI name in import statements.

fix

Use 'import cumm' instead of 'import cumm-cu126'.

affects: all

deprecatedcuMM versions before 0.7.0 used a different API with explicit gemm_ functions. The new API uses cumm.gemm directly.

fix

Upgrade to 0.8.2 and replace cumm.gemm_xx with cumm.gemm.

affects: <0.7.0

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'cumm'

Installed package 'cumm-cu126' but Python cannot find the module due to missing dependencies or incorrect import. Also, the module name is exactly 'cumm' (no hyphen).

fix

Run 'pip install cumm-cu126' and ensure you use 'import cumm' (no hyphen). Check that CUDA toolkit 12.6 is available.

RuntimeError: CUDA error: no kernel image is available for execution on the device

The GPU architecture is not supported by the precompiled kernels in cuMM. cuMM ships kernels for specific compute capabilities (e.g., sm_80, sm_86, sm_89, sm_90). Older or newer GPUs may not have a matching kernel.

fix

Use a supported GPU (e.g., NVIDIA Ampere, Ada Lovelace, Hopper) or rebuild cuMM from source with the appropriate architecture flags.

ImportError: libcudart.so.12: cannot open shared object file: No such file or directory

CUDA runtime library (libcudart.so.12) is not installed or not in the library path.

fix

Install CUDA 12.6 toolkit and add its lib64 directory to LD_LIBRARY_PATH.

Upgrade

Version history

0.8.2latest on PyPI · released May 28, 2025

Audit

Dependencies

No dependency data recorded yet.

Agent activity

9 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/FindDefinition/cumm ↗

packagehttps://pypi.org/project/cumm-cu126/ ↗