Thread Block and Grid Synchronization
Pre-Hopper: __syncthreads forced rigid, blocking barriers at the thread-block level.
Source: mortalapps.com- Pre-Hopper: __syncthreads() forced rigid, blocking barriers at the thread-block level.
- Modern CUDA supports Grid-level synchronization (this_grid().sync()).
- Asynchronous pipelines replace rigid barriers with mbarrier (Memory Barrier) objects.
- Decouples "arrival" from "waiting", enabling continuous execution.
Why This Matters
As kernels scale to span entire GPUs, forcing,000 threads to hard-stop and wait for memory fetches destroys throughput. Mastering modern synchronization allows infrastructure engineers to build persistent kernels and decoupled asynchronous pipelines that never truly halt execution.
Core Intuition
__syncthreads() is a red traffic light: everyone stops until it turns green. mbarrier is a restaurant pager: you place your order (async memory fetch), keep talking with your friends (independent compute), and only stop when the pager buzzes (wait on barrier) because you physically need the food (data) to eat.
Technical Deep Dive
Traditional synchronization used __syncthreads(). Cooperative Groups API generalized this via handles like this_thread_block(), coalesced_threads(), and this_grid(). this_grid().sync() allows a kernel to synchronize all SMs globally without dropping back to the CPU host, enabling persistent kernels (like persistent RNNs).
However, the architecture has shifted toward asynchronous barriers. An mbarrier object is initialized in shared memory. It tracks transaction counts in bytes. When a thread issues an asynchronous memory copy (via TMA), it links the copy to the mbarrier. The hardware DMA engine autonomously increments the barrier's completion count as bytes arrive.