@hackage accelerate-cuda0.13.0.2
Accelerate backend for NVIDIA GPUs
Categories
License
BSD-3-Clause
Maintainer
Trevor L. McDonell <tmcdonell@cse.unsw.edu.au>
Links
Versions
Deprecated
Tested Compilers
Dependencies (25)
- SafeSemaphore >=0.9 && <0.10
- Win32 >=2.2.1
- accelerate >=0.13 && <0.14
- array >=0.3 && <0.5
- base >=4 && <5
- binary >=0.5 && <0.7 Show all…
Dependents (13)
@hackage/accelerate-fourier, @hackage/meta-par-accelerate, @hackage/gloss-raster-accelerate, @hackage/parconc-examples, @hackage/acme-everything, @hackage/accelerate-cufft, Show all…-ddump-cc: print the generated code, kernel table management information, nvcc compiler warnings, and thread & resource statistics
-ddebug-cc: compile code with debugging symbols, suitable for 'cuda-gdb'
-ddump-exec: print each kernel name as it is invoked
-ddump-gc: print memory management information
-dverbose: other, uncategorised messages
-fflush-cache: delete the persistent kernel cache
Package Flags
debug
(off by default)
Enable tracing message flags. These are read from the command-line arguments, which is convenient but may cause problems interacting with the user program, so is not enabled by default. The available options:
bounds-checks
(on by default)
Enable bounds checking
unsafe-checks
(off by default)
Enable bounds checking in unsafe operations
internal-checks
(off by default)
Enable internal consistency checks
This library implements a backend for the Accelerate language instrumented for parallel execution on CUDA-capable NVIDIA GPUs. For further information, refer to the main Accelerate package: http://hackage.haskell.org/package/accelerate
To use this backend you will need:
A CUDA-enabled NVIDIA GPU with, for full functionality, compute capability 1.2 or greater. See the table on Wikipedia for supported GPUs: http://en.wikipedia.org/wiki/CUDA#Supported_GPUs
The CUDA SDK, available from the NVIDIA Developer Zone: http://developer.nvidia.com/cuda-downloads
See the Haddock documentation for additional information related to using this backend.
Compile modules that use the CUDA backend with the -threaded flag.