25 July 2014: CUDAfy 1.27 brings CUDA 6.0 support. You can get the installer from the downloads page or source code and zip file from Codeplex.
25 Mar 2014: GTC2014 kicks off in San Jose today. At 16:00 on Thursday in room 210C John Hauck will present C# with CUDAfy: Image Stitching Concepts.
24 Mar 2014: Once CUDA 6.0 is official CUDAfy will be updated to support it. Until that time please do not update.
29 Nov 2013: CUDAfy 1.26 is released today and brings SIMD functions, warp shuffle and support for classes.
11 Sep 2013: We really encourage CUDAfy users to consider taking a commercial license if you are making source code changes or want to embed the sources or library in your own application. Please remember that CUDAfy is LGPL. If you are complying with LGPL and CUDAfy is useful to you please donate to Harmony Through Education. This small charity is doing wonderful work at its school for handicapped children in India.
31 Aug 2013: CUDAfy 1.25 is here with CUDA 5.5 support, dynamic parallelism support and a new Cudafying process (backward compatible, but internally new with some new more flexible overloads that can take advantage of new system). Finally we have changed the commercial licenses so we can better support paying customers. You can see the new structure here. For those that were planning on purchasing under the old system then if you send an email before 7 September we can still supply at old prices (Single Developer €149, 5 Developer €499).
10 July 2013: We're working on a new more flexible way of Cudafying, dynamic parallelism support and will revamp the commercial licenses. There will be a new systems of licenses - more expensive actually but with clearer tiered benefits in a model familiar to many software tools.
12 June 2013: How to use a Xilinx FPGA evaluation board, a Mini-ITX motherboard, Intel Core CPU and a fast SSD to make a low cost data acquisition processing system with OpenCL support. Low Cost, High Performance FPGA and GPGPU Based Data Acquisition System
08 May 2013: An article called "Why use FPGAs for data acquisition systems?" has been posted in the new blog of this website. It's a good question considering that FPGAs are relatively tough to work with. But the sheer performance and relatively low price of new FPGA daughter cards makes the extra effort worthwhile.
07 May 2013: Version 1.22 of CUDAfy is the first official release with support for OpenCL. There are a bunch of bug fixes and other new features like integer intrinsics and code insertion.
23 Apr 2013: Benchmarking OpenCL and CUDA using CUDAfy on GTX Titan
- an article from John Michael Hauck where he tried CUDAfy on GTX Titan in both CUDA and OpenCL mode. He also compares against the .NET parallel library on a 8-core Xeon CPU. An entertained read.
17 Apr 2013: A range of high performance digitizers and waveform generators
(ADCs and DACs) are now featured on this website. When used with supported Xilinx FPGA cards
and PCI-Express drivers fast, low latency transfers can be made to and from NVIDIA GPUs using ourGPUDirect
16 Apr 2013: V1.21 Beta
is supplied with an installer that also checks your system is correctly configured for OpenCL and/or CUDA targets.
04 Mar 2013: V1.20 Beta with new OpenCL support is available on the download page or codeplex. For many applications you only need to change a singe enum to target an AMD GPU or Intel CPU. Remember to install the relevant OpenCL SDK from AMD or Intel! Have fun and let us know how you get on.
25 Jan 2013: CUDAfy featured on Dotnet Rocks. Carl and Richard interview Evan Hauck. Listen to the show here
. Interview is at about 5 minutes from start.
22 Jan 2013: NVIDIA GPUDirect
support is available for 4DSP FPGA and I/O cards (ADCs, DACs, frame grabbers). Using GPUDirect improves bandwidth and reduces latency between GPUs and the 4DSP cards. Email or phone
for more info.
14 Jan 2013: CUDAfy featured at CodeMash 2013
with John and Evan Hauck.
13 Jan 2013: We're working on OpenCL support and so far it's looking good. This will allow CUDAfy applications to work on AMD GPUs as well as Intel and AMD CPUs. Little or no change is required to current CUDAfy apps. If you'd like to beta-test then please get in touch
16 Nov 2012: Binomial Option Pricing sample available - This finance sample project is based on the NVIDIA CUDA C sample of the same name. When compared to the CUDA C code it demonstrates just how easy writing CUDAfy applications is. A beta of CUDAfy V1.13 is included (allows non-public methods and members to be CUDAfied). CUDA 5.0 and a GPU with compute 1.3 or greater is required.http://cudafy.codeplex.com/documentation