The slow-down of technology scaling and the emergence of Artificial Intelligence (AI) workloads have led computer architects to increasingly exploit parallelization coupled with hardware acceleration to keep pushing the performance envelope. However, this solution comes with the challenge of synchronization of processing elements (PEs) in massive heterogeneous many-core platforms. To address this challenge, we propose FractalSync, a hardware accelerated synchronization mechanism for Bulk Synchronous Parallel (BSP) systems. We integrate FractalSync in MAGIA, a scalable tile-based AI accelerator, with each tile featuring a RISC-V-coupled matrix-multiplication (MatMul) accelerator, scratchpad memory (SPM), and a DMA connected to a global mesh Network-on-Chip (NoC). We study the scalability of the proposed barrier synchronization scheme on tile meshes ranging from 2 × 2 PEs to 16 × 16 PEs to evaluate its design boudaries. Compared to a synchronization scheme based on software atomic memory operations (AMOs), the proposed solution achieves up to 43 × speedup on synchronization, introducing a negligible area overhead (). FractalSync closes timing at MAGIA's target 1GHz frequency.
Isachi, V., Nadalini, A., Gallotta, R.F., Garofalo, A., Conti, F., Rossi, D. (2025). FractalSync: Lightweight Scalable Global Synchronization of Massive Bulk Synchronous Parallel AI Accelerators. 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES : Association for Computing Machinery, Inc [10.1145/3719276.3725203].
FractalSync: Lightweight Scalable Global Synchronization of Massive Bulk Synchronous Parallel AI Accelerators
Isachi, Victor;Nadalini, Alessandro;Garofalo, Angelo;Conti, Francesco;Rossi, Davide
2025
Abstract
The slow-down of technology scaling and the emergence of Artificial Intelligence (AI) workloads have led computer architects to increasingly exploit parallelization coupled with hardware acceleration to keep pushing the performance envelope. However, this solution comes with the challenge of synchronization of processing elements (PEs) in massive heterogeneous many-core platforms. To address this challenge, we propose FractalSync, a hardware accelerated synchronization mechanism for Bulk Synchronous Parallel (BSP) systems. We integrate FractalSync in MAGIA, a scalable tile-based AI accelerator, with each tile featuring a RISC-V-coupled matrix-multiplication (MatMul) accelerator, scratchpad memory (SPM), and a DMA connected to a global mesh Network-on-Chip (NoC). We study the scalability of the proposed barrier synchronization scheme on tile meshes ranging from 2 × 2 PEs to 16 × 16 PEs to evaluate its design boudaries. Compared to a synchronization scheme based on software atomic memory operations (AMOs), the proposed solution achieves up to 43 × speedup on synchronization, introducing a negligible area overhead (). FractalSync closes timing at MAGIA's target 1GHz frequency.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


