////////////////////////////////////////////////////////////////////////////////
// Potential occupancy calculator
//
// The potential occupancy is calculated according to the kernel and
// execution configuration the user desires. Occupancy is defined in
// terms of active blocks per multiprocessor, and the user can convert
// it to other metrics.
//
// This wrapper routine computes the occupancy of kernel, and reports
// it in terms of active warps / maximum warps per SM.
////////////////////////////////////////////////////////////////////////////////
static double reportPotentialOccupancy(int blockSize, SizeT dynamicSMem)
{
int device;
int numBlocks;
int activeWarps;
int maxWarps;
double occupancy;
CudaOccupancy.cudaOccDeviceProp prop = new CudaOccupancy.cudaOccDeviceProp(0);
CudaOccupancy.cudaOccResult result = new CudaOccupancy.cudaOccResult();
CudaOccupancy.cudaOccFuncAttributes attributes = new CudaOccupancy.cudaOccFuncAttributes(kernel);
CudaOccupancy.cudaOccDeviceState state = new CudaOccupancy.cudaOccDeviceState();
state.cacheConfig = CudaOccupancy.cudaOccCacheConfig.PreferNone;
CudaOccupancy.cudaOccMaxActiveBlocksPerMultiprocessor(result, prop, attributes, state, blockSize, dynamicSMem);
numBlocks = result.ActiveBlocksPerMultiProcessor;
activeWarps = numBlocks * blockSize / prop.warpSize;
maxWarps = prop.maxThreadsPerMultiProcessor / prop.warpSize;
occupancy = (double)activeWarps / maxWarps;
return(occupancy);
}
////////////////////////////////////////////////////////////////////////////////
// Occupancy-based launch configurator
//
// The launch configurator, cudaOccupancyMaxPotentialBlockSize and
// cudaOccupancyMaxPotentialBlockSizeVariableSMem, suggests a block
// size that achieves the best theoretical occupancy. It also returns
// the minimum number of blocks needed to achieve the occupancy on the
// whole device.
//
// This launch configurator is purely occupancy-based. It doesn't
// translate directly to performance, but the suggestion should
// nevertheless be a good starting point for further optimizations.
//
// This function configures the launch based on the "automatic"
// argument, records the runtime, and reports occupancy and runtime.
////////////////////////////////////////////////////////////////////////////////
static int launchConfig(CudaDeviceVariable <int> array, int arrayCount, bool automatic)
{
int blockSize = 0;
int minGridSize = 0;
int gridSize;
SizeT dynamicSMemUsage = 0;
float elapsedTime;
double potentialOccupancy;
CudaOccupancy.cudaOccDeviceState state = new CudaOccupancy.cudaOccDeviceState();
state.cacheConfig = CudaOccupancy.cudaOccCacheConfig.PreferNone;
if (automatic)
{
CudaOccupancy.cudaOccMaxPotentialOccupancyBlockSize(ref minGridSize, ref blockSize, new CudaOccupancy.cudaOccDeviceProp(0), new CudaOccupancy.cudaOccFuncAttributes(kernel), state, dynamicSMemUsage);
Console.WriteLine("Suggested block size: {0}", blockSize);
Console.WriteLine("Minimum grid size for maximum occupancy: {0}", minGridSize);
}
else
{
// This block size is too small. Given limited number of
// active blocks per multiprocessor, the number of active
// threads will be limited, and thus unable to achieve maximum
// occupancy.
//
blockSize = manualBlockSize;
}
// Round up
//
gridSize = (arrayCount + blockSize - 1) / blockSize;
// Launch and profile
//
kernel.GridDimensions = gridSize;
kernel.BlockDimensions = blockSize;
elapsedTime = kernel.Run(array.DevicePointer, arrayCount);
// Calculate occupancy
//
potentialOccupancy = reportPotentialOccupancy(blockSize, dynamicSMemUsage);
Console.WriteLine("Potential occupancy: {0}%", potentialOccupancy * 100);
// Report elapsed time
//
Console.WriteLine("Elapsed time: {0}ms", elapsedTime * 100);
return(0);
}
