Displaying 8 results from an estimated 8 matches for "blockdim".
2020 Sep 23
2
Information about the number of indices in memory accesses
...and stores without a GEP operand, explicitly create a
(trivial) GEP with index 0
So now the operand of every load and store is a GEP instruction.
For simple stuff i am getting the right answer but when the index
expression becomes more complex multiple GEPs are introduced. For instance:
*(A+2*(blockDim.x*blockIdx.x+threadIdx.x+1)+2+3) = 5;
produces:
%6 = call i32 @llvm.nvvm.read.ptx.sreg.ntid.x()
%7 = call i32 @llvm.nvvm.read.ptx.sreg.ctaid.x()
%8 = mul i32 %6, %7,
%9 = call i32 @llvm.nvvm.read.ptx.sreg.tid.x()
%10 = add i32 %8, %9,
%11 = add i32 %10, 1,
%12 = mul i32 2, %1...
2020 Oct 03
2
Information about the number of indices in memory accesses
...dex 0
> >
> > So now the operand of every load and store is a GEP instruction.
> >
> > For simple stuff i am getting the right answer but when the index
> > expression becomes more complex multiple GEPs are introduced. For
> > instance:
> >
> > *(A+2*(blockDim.x*blockIdx.x+threadIdx.x+1)+2+3) = 5;
> >
> > produces:
> >
> > %6 = call i32 @llvm.nvvm.read.ptx.sreg.ntid.x()
> > %7 = call i32 @llvm.nvvm.read.ptx.sreg.ctaid.x()
> > %8 = mul i32 %6, %7,
> > %9 = call i32 @llvm.nvvm.read.ptx.sreg.tid.x()
> >...
2020 Oct 03
2
Information about the number of indices in memory accesses
...every load and store is a GEP instruction.
>>> >
>>> > For simple stuff i am getting the right answer but when the index
>>> > expression becomes more complex multiple GEPs are introduced. For
>>> > instance:
>>> >
>>> > *(A+2*(blockDim.x*blockIdx.x+threadIdx.x+1)+2+3) = 5;
>>> >
>>> > produces:
>>> >
>>> > %6 = call i32 @llvm.nvvm.read.ptx.sreg.ntid.x()
>>> > %7 = call i32 @llvm.nvvm.read.ptx.sreg.ctaid.x()
>>> > %8 = mul i32 %6, %7,
>>> >...
2012 Feb 23
0
[LLVMdev] Clang support for CUDA
Hi,
I am trying to convert a simple CUDA program to LLVM IR using clang 3.0.
The program is as follows,
#include<stdio.h>
#nclude<clang/test/SemaCUDA/cuda.h>
__global__ void kernfunc(int *a)
{
*a=threadIdx.x+blockIdx.x*blockDim.x;
}
int main()
{
int *h_a,*d_a,n;
n=sizeof(int);
h_a=(int*)malloc(n);
*h_a=5;
cudaMalloc((void*)&d_a,n);
cudaMemcpy(d_a,h_a,n,cudaMemcpyHostToDevice);
kernelfunc<<<1,1>>>(d_a);
cudaMemcpy(h_a,d_a,n,cudaMemcpyDeviceToHost);
printf("%d",*h_a);
return 0;
}
What a...
2016 Mar 09
2
RFC: Proposing an LLVM subproject for parallelism runtime and support libraries
...f related operations on a stream, as in the following code
snippet:
.. code-block:: c++
se::Stream stream(executor);
se::Timer timer(executor);
stream.InitWithTimer(&timer)
.ThenStartTimer(&timer)
.ThenLaunch(se::ThreadDim(dim_block_x, dim_block_y),
se::BlockDim(dim_grid_x, dim_grid_y),
my_kernel,
arg0, arg1, arg2)
.ThenStopTimer(&timer)
.BlockHostUntilDone();
The name of the kernel being launched in the snippet above is `my_kernel`
and the arguments being passed to the kernel are `arg0`, `arg1`, and
`ar...
2016 Mar 09
2
RFC: Proposing an LLVM subproject for parallelism runtime and support libraries
...owing
> code snippet:
>
> .. code-block:: c++
>
> se::Stream stream(executor);
> se::Timer timer(executor);
> stream.InitWithTimer(&timer)
> .ThenStartTimer(&timer)
> .ThenLaunch(se::ThreadDim(dim_block_x, dim_block_y),
> se::BlockDim(dim_grid_x, dim_grid_y),
> my_kernel,
> arg0, arg1, arg2)
> .ThenStopTimer(&timer)
> .BlockHostUntilDone();
>
> The name of the kernel being launched in the snippet above is `my_kernel`
> and the arguments being passed to the...
2016 Mar 10
2
RFC: Proposing an LLVM subproject for parallelism runtime and support libraries
...t;> .. code-block:: c++
>>
>> se::Stream stream(executor);
>> se::Timer timer(executor);
>> stream.InitWithTimer(&timer)
>> .ThenStartTimer(&timer)
>> .ThenLaunch(se::ThreadDim(dim_block_x, dim_block_y),
>> se::BlockDim(dim_grid_x, dim_grid_y),
>> my_kernel,
>> arg0, arg1, arg2)
>> .ThenStopTimer(&timer)
>> .BlockHostUntilDone();
>>
>> The name of the kernel being launched in the snippet above is `my_kernel`
>> and the ar...
2012 Jul 21
3
Use GPU in R with .Call
...function and the kernel are in a *SEPARATE* file
called "VecAdd_kernel.cu".
=======================file VecAdd_kernel.cu========================
#define THREAD_PER_BLOCK 100
__global__ void VecAdd(double *a,double *b, double *c,int len) {
int idx = threadIdx.x + blockIdx.x * blockDim.x;
if (idx<len){
c[idx] = a[idx] + b[idx];
}
}
void vecAdd_kernel(double *ain,double *bin,double *cout,int len){
int alloc_size;
alloc_size=len*sizeof(double);
/*Step 0a) Make a device copies of ain,bin,and cout.*/
double *a_copy,*b_copy,*cout_copy;
/*Step 0b) Alloca...