Skip to main content
Join the official Python Developers Survey 2018 and win valuable prizes: Start the survey!

CUDA cffi bindings and helper classes

Project description

cuda4py
=========

Python cffi CUDA bindings and helper classes.

Tested with Python 2.7, Python 3.6 and PyPy on Linux with CUDA 8.0.

To compile kernel code written in C++, nvcc should be in PATH and
exported functions should be marked as extern "C"
(for Windows, cl.exe should be in PATH also).
Functions in plain PTX can be used without nvcc.

To use CUBLAS, libcublas.so (cublas64_65.dll) should be present.
To use CUDNN, libcudnn.so (cudnn64_65.dll) should be present.
To use CUFFT, libcufft.so (cufft64_65.dll) should be present.
To use CURAND, libcurand.so (curand64_65.dll) should be present.

Not all CUDA api is currently covered.

To install the module run:
```bash
python setup.py install
```
or just copy src/cuda4py to any place where python
interpreter will be able to find it.

To run the tests, execute:

for Python 2.7:
```bash
PYTHONPATH=src nosetests -w tests
```

for Python 3.4:
```bash
PYTHONPATH=src nosetests3 -w tests
```

for PyPy:
```bash
PYTHONPATH=src pypy -m nose -w tests
```

Example usage:

```python
import cuda4py as cu
import logging
import numpy


if __name__ == "__main__":
logging.basicConfig(level=logging.DEBUG)
ctx = cu.Devices().create_some_context()
module = cu.Module(
ctx, source=
"""
extern "C"
__global__ void test(const float *a, const float *b,
float *c, const float k) {
size_t i = blockDim.x * blockIdx.x + threadIdx.x;
c[i] = (a[i] + b[i]) * k;
}
""")
test = cu.Function(module, "test")
a = numpy.arange(1000000, dtype=numpy.float32)
b = numpy.arange(1000000, dtype=numpy.float32)
c = numpy.empty(1000000, dtype=numpy.float32)
k = numpy.array([0.5], dtype=numpy.float32)
a_buf = cu.MemAlloc(ctx, a)
b_buf = cu.MemAlloc(ctx, b)
c_buf = cu.MemAlloc(ctx, c)
test.set_args(a_buf, b_buf, c_buf, k)
test((a.size, 1, 1))
c_buf.to_host(c)
max_diff = numpy.fabs(c - (a + b) * k[0]).max()
logging.info("max_diff = %.6f", max_diff)
```

Released under Simplified BSD License.
Copyright (c) 2014, Samsung Electronics Co.,Ltd.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
cuda4py-1.4.4.tar.gz (58.3 kB) Copy SHA256 hash SHA256 Source None Mar 19, 2017

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page