Distributed Job Allocation for Large-Scale Manycores

Contemporary operating systems heavily rely on single system images with shared memory constructs that may not scale well to large core counts. We consider the challenge of distributed job allocation, where each job is comprised of a set of tasks to be mapped to disjoint cores. A naive solution performing fragmented allocations may quickly escalate to deadlocks, where jobs hold and wait for cores in circular dependencies. To tackle these challenges, we propose a deadlock free distributed job allocation protocol. We have devised two policies for avoiding deadlocks, namely active cancellation and sequencer-based atomic broadcast. The protocol and the two policies have been implemented and evaluated on a Tilera TilePro64 processor with 64 cores on a single socket. Results show sparse job allocations to incur lower overhead for active cancellation while sequencer-based atomic broadcast has less overhead for denser allocations.