Agile Queue: A Fast Scalable Concurrent FIFO Queue on GPU
Md. Sabbir Hossain Polak, David Troendle, Byunghyun Jang · 2024
This work presents Agile Queue, a queue specifically designed to support high concurrency on modern GPUs. At its core is to replace conflicting accesses to shared objects with independent accesses to private data. The proposed Agile queue operates on two different granularity - thread block and warp. While the thread block granularity exploits better parallelism among threads, it requires a synchronization primitive to designate a master thread. The warp granularity, on the other hand, leverages work sharing strategy among threads in a warp without any synchronization, which reduces the inherent branch divergence. Both variants support the wrap-around of the head and tail across the ring buffer. Each request to the ring buffer generates a ticket for strict ordering without fully blocking at queue boundary conditions. While the thread block variant utilizes shared memory to reduce global memory accesses, the warp variant broadcasts the offset to all other lanes in the warp by the leader (first active) thread within the warp. Our experiments demonstrate the superior performance and scalability of the Agile queue over existing solutions. Specifically it outperforms the BWD (Broker Queue Work Distributor), the fastest GPU queue to our knowledge, by more than 2 × without compromising FIFO semantics.