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# Thread identifier

CUDA threads are organized hierarchically into blocks, and these blocks are further organized into a grid. To efficiently map threads to data elements in parallel programming, CUDA provides a way to identify each thread uniquely using three built-in variables:

1. `threadIdx.x`: This variable identifies the thread’s index within a block. In a 1D block, `threadIdx.x` ranges from `0` to `blockDim.x - 1`.
2. `blockDim.x`: This variable represents the total number of threads in each block along the x-axis. It is a constant value for all blocks within the grid.
3. `blockIdx.x`: This variable identifies the block’s index within the grid along the x-axis. In a 1D grid, `blockIdx.x` ranges from `0` to `gridDim.x - 1`, where `gridDim.x` is the total number of blocks in the grid along the x-axis.

## Compute a unique index

Each thread in the grid can be uniquely identified by a combination of these three variables. The most common way to compute a unique index for a thread in a 1D execution is by combining these values as follows:

    int idx = threadIdx.x + blockIdx.x * blockDim.x;

## Preventing out-of-bounds access

The number of threads you launch might not perfectly match the number of tasks or data elements you want to process. For example, if you have a small number of tasks (`num_tasks`), but you launch a large number of threads, some of those threads would end up with no valid data to process.

By checking if `idx` is greater than or equal to `num_tasks`, we can ensure that only the threads with valid work continue processing. This check effectively “turns off” threads that don’t have anything to do, allowing the program to run safely and correctly.

    if (idx >= num_tasks) return;