Need help with kgpu?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

208 Stars 30 Forks GNU General Public License v2.0 145 Commits 5 Opened issues


Currently GPUstore. Technical paper:

Services available


Need anything else?

Contributors list

# 304,636
4 commits
 KGPU - Augmenting Linux with GPUs

** Important note:

 A new branch 'k32' is created for KGPU compilation on 3.x kernels,
 I tested 3.2.16. If you want to try KGPU on recent kernels, definitely
 checkout that branch.

I don't have time to modify everything to comply with the latest kernel, so k32 branch has gaes and raid6 services disabled. Just leaves an example service for hubbyists to borrow code to start with their own service development.

What is it?

 Treating the GPU as a computing co-processor. To enable the
 data-parallel computation inside the Linux kernel. Using SIMD (or
 SIMT in CUDA) style code to accelerate Linux kernel

Make the Linux kernel really parallelized: which is not only processing multiple requests concurrently, but can also partition a single large requested computation into tiles and do them on GPU cores.

GPU can give the OS kernel dedicated cores that can be fully occupied by the kernel. But the multicore CPUs should not be occupied by the kernel because other tasks also need them.

KGPU is not an OS running on GPU, which is almost impossible because of the limited functionality of current GPU architectures. KGPU tries to enable vector computing for the kernel.

To access the code, using git to clone: [email protected]:wbsun/kgpu.git or goto .

As for copyright license, we use GPLv2.

News * RAID6 PQ computing function added as a service, gpq module for its kernel part to replace the global raid6call algorithm with GPU one, it can beat the fastest SSE version with 16 disks and >= 1MB data on my machine. Try it with a RAID6 on dm driver. * Scripts to run and stop kgpu. * Simple build system. * dm-crypt can use gaesecb or gaes_ctr directly.

Try it?

We use GTX480. You don't need such high-end video
    card, but you should have a NVIDIA card that support CUDA
    computing capability 2.0 or higher.  If you don't have more
    than 1G video memory, change KGPU_BUF_SIZE in kgpu/kgpu.h to
    make sure KGPU_BUF_SIZE*2 < Size of Your Video
    Memory - (x) where the max of x is a value that you need try
    some times to figure out. Or simply leave x = 64M or 128M.

Notice a new change: we enabled a new feature to allow KGPU remapping any kernel pages into CUDA page-locked memory, the remapping also need video memory on the GPU side, so now there are two GPU buffers with the same size, which is KGPU_BUF_SIZE. So KGPU_BUF_SIZE should be <= video memory size/2.

Software: We compile the CUDA code with nvcc in CUDA 4.0. The OS kernel is vanilla Linux You MUST use a 64bit linux kernel compiled targeting at x86_64!

Make and Run it: Check out the code from Github or download the archive from Google Code and extract files into say kgpu directory: cd kgpu && make all

Now all outputs are in build directory. To run it: cd build && sudo ./runkgpu

This only starts KGPU module, helper and loads AES ciphers. To use modified eCryptfs and dm-crypt, in the build directory: sudo insmod ./ecryptfs.ko && sudo insmod ./dm-crypt


To stop it: Umount your eCryptfs partition, delete dm-crypt mappers and: sudo rmmod ecryptfs && sudo rmmod dm-crypt Stop "helper" program by Ctrl-C sudo ./stopkgpu (in build/)

Weibin Sun, Xing Lin {wbsun, xinglin}

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.