thread block

**Thread block** is the **cooperating group of GPU threads that executes on one SM and shares synchronization and local memory resources** - it is the core work unit for organizing cooperation, reuse, and locality in CUDA kernels. **What Is Thread block?** - **Definition**: Fixed-size thread group with shared-memory scope and barrier synchronization capability. - **Execution Mapping**: A block is scheduled on a single SM and may run concurrently with other resident blocks. - **Coordination Tools**: Threads can communicate through shared memory and synchronize via block barriers. - **Size Constraints**: Block dimensions are limited by architecture maximum threads and resource budgets. **Why Thread block Matters** - **Data Reuse**: Block-level collaboration reduces redundant global memory access. - **Synchronization**: Many parallel algorithms rely on intra-block barriers for correctness. - **Performance**: Block shape influences occupancy, memory coalescing, and scheduler effectiveness. - **Algorithm Design**: Choosing right block decomposition is central to efficient GPU kernel structure. - **Portability**: Well-designed block patterns adapt better across changing SM resource limits. **How It Is Used in Practice** - **Shape Selection**: Match block dimensions to data layout and shared-memory tiling strategy. - **Resource Budgeting**: Tune register and shared-memory use so enough blocks can reside concurrently. - **Correctness Checks**: Verify barrier placement and shared-memory indexing to avoid race conditions. Thread block design is **the building block of efficient CUDA parallelization** - effective intra-block cooperation is critical for both correctness and high GPU performance.