gpucoder.atomicCAS - Atomically compare and swap the value of a variable in global or shared
memory - MATLAB ([original](https://in.mathworks.com/help/gpucoder/ref/gpucoder.atomiccas.html)) ([raw](?raw))
Atomically compare and swap the value of a variable in global or shared memory
Since R2021b
Syntax
Description
[A,oldA] = gpucoder.atomicCAS([A](#mw%5Fe9d9ebed-1d2e-4a4a-b334-74d763ce88a4),[B](#mw%5Fe9d9ebed-1d2e-4a4a-b334-74d763ce88a4),[C](#mw%5Fe9d9ebed-1d2e-4a4a-b334-74d763ce88a4))
compares B
to the value of A
in global or shared memory and if the values are the same writes the value of C
into A. The operation is atomic in a sense that the entire read-modify-write operation is guaranteed to be performed without interference from other threads. The order of the input and output arguments must match the syntax provided.
Examples
Perform a simple atomic compare and swap operation by using thegpucoder.atomicCAS
function and generate CUDA® code that calls corresponding CUDAatomicCAS()
APIs.
In one file, write an entry-point function myAtomicCAS
that accepts matrix inputs a
,b
, andc
.
function a = myAtomicCAS(a,b,c)
coder.gpu.kernelfun; for i =1:numel(a) [a(i),~] = gpucoder.atomicCAS(a(i), b, c); end
end
To create a type for a matrix of doubles for use in code generation, use thecoder.newtype function.
A = coder.newtype('uint32', [1 30], [0 1]); B = coder.newtype('uint32', [1 1], [0 0]); C = coder.newtype('uint32', [1 1], [0 0]); inputArgs = {A,B,C};
To generate a CUDA library, use the codegen function.
cfg = coder.gpuConfig('lib'); cfg.GenerateReport = true;
codegen -config cfg -args inputArgs myAtomicCAS -d myAtomicCAS
The generated CUDA code contains the myAtomicCAS_kernel1
kernel with calls to the atomicCAS()
CUDA APIs.
// // File: myAtomicCAS.cu // ...
static global launch_bounds(1024, 1) void myAtomicCAS_kernel1( const uint32_T c, const uint32_T b, const int32_T i, uint32_T a_data[]) { uint64_T loopEnd; uint64_T threadId;
...
for (uint64_T idx{threadId}; idx <= loopEnd; idx += threadStride) { int32_T b_i; b_i = static_cast(idx); atomicCAS(&a_data[b_i], b, c); } } ...
void myAtomicCAS(uint32_T a_data[], int32_T a_size[2], uint32_T b, uint32_T c) { dim3 block; dim3 grid; ...
if (validLaunchParams) { cudaMemcpy(gpu_a_data, a_data, a_size[1] * sizeof(uint32_T), cudaMemcpyHostToDevice); myAtomicCAS_kernel1<<<grid, block>>>(c, b, i, gpu_a_data); cudaMemcpy(a_data, gpu_a_data, a_size[1] * sizeof(uint32_T), cudaMemcpyDeviceToHost); ...
}
Input Arguments
Operands, specified as scalars, vectors, matrices, or multidimensional arrays. Inputs A
, B
, and C
must satisfy the following requirements:
- Have the same data type.
- Have the same size or have sizes that are compatible. For example,
A
is anM
-by-N
matrix andB,C
is a scalar or1
-by-N
row vector.
Data Types: int32
| uint32
| uint64
Version History
Introduced in R2021b
See Also
Functions
- gpucoder.atomicAdd | gpucoder.atomicDec | gpucoder.atomicExch | gpucoder.atomicInc | gpucoder.atomicMax | gpucoder.atomicMin | gpucoder.atomicSub