A scalable hash scheduler for decoding of multiple H.264/AVC streams on multi-core architecture

Existing scheduling schemes for decoding H.264/AVC multiple streams on multi-core are largely limited by ineffective use of multi-core architecture. Among the reasons are inefficient load balancing, in which common load metrics (e.g. tasks, frames, bytes) are unable to correctly reflect processing load at cores, unscalability of scheduling algorithms for a large scale multi-core, and bottlenecks at schedulers for multi-stream decoding. In this paper, we propose a scalable adaptive Highest Random Weight (HA-HRW) hash scheduler for distributed shared memory multi-core architecture considering the following: 1) memory access and core/cache topology of the multi-core architecture; 2) appropriate processing time load metric to enforce a true load balancing; 3) hierarchical parallel scheduling to decode multiple streams simultaneously; 4) locality characteristics of processing unit candidate to limit search within neighboring cores to enable scalable scheduling. We implement and evaluate our approach on a 32-core SGI server with realistic workload. Comparing with existing schemes, our scheme achieves higher throughput, better load balancing, better CPU utilization, and no jitter problem. Our scheme scales with multi-core and multiple streams as its time complexity is O(1).