What is blockDim X in CUDA?

What is blockDim X in CUDA?

x (is the number of blocks), blockDim. x (is the number of threads in each block), blockIdx. x (is the index of the current block within the grid), and threadIdx.

What is blockIdx and threadIdx?

Basically, the blockIdx.x variable is similar to the thread index except it refers to the number associated with the block. Let’s say you want 2 blocks in a 1D grid with 5 threads in each block. Your threadIdx.x would be 0, 1,…, 4 for each block and your blockIdx.x would be 0 and 1 depending on the specific block.

What does blockDim X contain?

blockDim: This variable and contains the dimensions of the block. threadIdx: This variable contains the thread index within the block. x line would in effect be the unique index of each thread within your grid.

What is the datatype of blockDim and gridDim?

CUDA uses the vector type dim3 for the dimension variables, gridDim and blockDim. We use dim3 variables for specifying execution configuration. CUDA uses the vector type dim3 for the dimension variables, gridDim and blockDim. CUDA uses the vector type uint3 for the index variables, blockIdx and threadIdx.

What is __ global __ In CUDA?

__global__ is a CUDA C keyword (declaration specifier) which says that the function, Executes on device (GPU) Calls from host (CPU) code.

What is cuBLAS?

The cuBLAS Library provides a GPU-accelerated implementation of the basic linear algebra subroutines (BLAS). cuBLAS accelerates AI and HPC applications with drop-in industry standard BLAS APIs highly optimized for NVIDIA GPUs. The cuBLAS library is included in both the NVIDIA HPC SDK and the CUDA Toolkit.

Where do I find CUDA thread ID?

Each CUDA card has a maximum number of threads in a block (512, 1024, or 2048). Each thread also has a thread id: threadId = x + y Dx + z Dx Dy The threadId is like 1D representation of an array in memory. If you are working with 1D vectors, then Dy and Dz could be zero.

What is grid in CUDA?

CUDA blocks are grouped into a grid. A kernel is executed as a grid of blocks of threads (Figure 2). Each kernel is executed on one device and CUDA supports running multiple kernels on a device at one time. Figure 3 shows the kernel execution and mapping on hardware resources available in GPU.

Is device only callable?

__device__ functions can be called only from the device, and it is executed only in the device. __global__ functions can be called from the host, and it is executed in the device. Therefore, you call __device__ functions from kernels functions, and you don’t have to set the kernel settings.

What is warp CUDA?

In CUDA, groups of threads with consecutive thread indexes are bundled into warps; one full warp is executed on a single CUDA core. At runtime, a thread block is divided into a number of warps for execution on the cores of an SM. Therefore, blocks are divided into warps of 32 threads for execution. …

How do you write a CUDA kernel?

CUDA Programming Model Basics

1. Declare and allocate host and device memory.
2. Initialize host data.
3. Transfer data from the host to the device.
4. Execute one or more kernels.
5. Transfer results from the device to the host.

What is compute capability?

The compute capability is the “feature set” (both hardware and software features) of the device. You may have heard the NVIDIA GPU architecture names “Tesla”, “Fermi” or “Kepler”. Each of those architectures have features that previous versions might not have.

When to create a loop in CUDA griddim?

In particular, when the total threads in the x-dimension ( gridDim.x*blockDim.x) is less than the size of the array I wish to process, then it’s common practice to create a loop and have the grid of threads move through the entire array.

How many blocks are in a grid in CUDA?

You seem to be a bit confused about the thread hierachy that CUDA has; in a nutshell, for a kernel there will be 1 grid, (which I always visualize as a 3-dimensional cube). Each of its elements is a block, such that a grid declared as dim3 grid (10, 10, 2); would have 10*10*2 total blocks.

Why does CUDA give each thread a unique threadId?

CUDA gives each thread a unique ThreadID to distinguish between each other even though the kernel instructions are the same. In our example, in the kernel call the memory arguments specify 1 block and N threads.

What’s the difference between blockIdx and griddim?

gridDim: This variable contains the dimensions of the grid. blockIdx: This variable contains the block index within the grid. blockDim: This variable and contains the dimensions of the block.