A warp or wavefront is a logical unit in GPU kernel scheduling - the largest set of threads within the grid which are (logically) instruction-locked and always synchronized with each other..
With CUDA's shfl.idx instruction, we perform what is essentially an intra-warp gather: Each lane provides a datum and an origin lane, and gets the datum of the origin lane.
What about the converse operation, scatter? I mean, not scattering to…
I have query about following question:
Suppose, we have a 9*7 picture (7 pixels in the x direction and 9 pixels in the y direction), how many warps will have control divergence assuming block of 4*4 threads and 8 threads per warp?
How will the…
My understanding is that warp is a group of threads that defined at runtime through the task scheduler, one performance critical part of CUDA is the divergence of threads within a warp, is there a way to make a good guess of how the hardware will…
When a warp finishes a kernel, but another warp of the same block is still running, will the finished warp be blocked until the other warps of the same block finish, or will the finished warp be available for immediate reuse by another block while…
NVIDIA GPUs have schedule complete warps to execute instructions together (well, sort of; see also this question). Thus, if we have a "linear" block of, say, 90 threads (or X x Y x Z = 90 x 1 x 1) - a GPU core will have three warps to schedule…
cuda-memcheck has detected a race condition in the code that does the following:
condition = /*different in each thread*/;
shared int owner[nWarps];
/* ... owner[i] is initialized to blockDim.x+1 */
if(condition) {
owner[threadIdx.x/32] =…
I need to make a warp shuffling that look like this:
On this picture, the number of threads is limited to 8 to make it readable.
If I read the Nvidia SDK and ptx manual, the shuffle instruction should do the job, specially the shfl.idx.b32 d[|p],…
In recent nVIDIA GPU uarchitectures, a single streaming multiprocessor seems to be broken up into 4 sub-units; with each of them having horizontal or vertical 'bars' of 8 'squares', corresponding to different functional units: integer ops, 32-bit…
I have been using CUDA for a month, now i'm trying to make it clear that how many warps/blocks are needed to hide the latency of memory accesses. I think it is related to the maximum of resident warps on a multiprocessor.
According to Table.13 in…
nvcc device code has access to a built-in value, warpSize, which is set to the warp size of the device executing the kernel (i.e. 32 for the foreseeable future). Usually you can't tell it apart from a constant - but if you try to declare an array…
I have a question about the warps in GPU.
I used the following configuration:
GeForce 210
Cuda capability major/minor : 1.2
2 multiprocessors, 8 CUDA Cores/MP : 16 CUDA Cores
Warp size : 32
Below are the running times (I used…
I'm trying to update some older CUDA code (pre CUDA 9.0), and I'm having some difficulty updating usage of warp shuffles (e.g., __shfl).
Basically the relevant part of the kernel might be something like this:
int f = d[threadIdx.x];
int warpLeader =…
I implemented some CUDA code. It runs fine but the alogrithm inherently produces a strong thread divergence. This is expected.
I will later try to reduce divergence. But for the moment I would be happy to be able to measure it.
Is there an easy way…
I have a Nvidia GeForce GTX 960M graphics card, which has the following specs:
Multiprocessors: 5
Cores per multiprocessor: 128 (i.e. 5 x 128 = 640 cores in total)
Max threads per multiprocessor: 2048
Max block size (x, y, z): (1024, 1024,…
Following host code test.c and device code test0.cu are intended to give the same result.
test.c
$ cat test.c
#include
#include
int main()
{
int data[32];
int dummy[32];
for (int i = 0; i < 32; i++)
…
