Task-FIFO co-scheduling of streaming applications on MPSoCs with predictable memory hierarchy

This article studies the scheduling of real-time streaming applications on multiprocessor systems-on-chips with predictable memory hierarchy. An iteration-based task-FIFO co-scheduling framework is proposed for this problem. We obtain FIFO size distributions using Pareto space searching, based on which the task-toprocessor mapping is obtained with the potential FIFO allocation being taken into account; then, the FIFOto-memory allocation is optimized to minimize the total memory access cost; finally, a self-timed throughput analysis method that considers memory and direct memory access controller contention is utilized to analyze the throughput. Our methods are validated by a set of synthesized and practical applications on different platforms

Task-FIFO co-scheduling of streaming applications on MPSoCs with predictable memory hierarchy

This article studies the scheduling of real-time streaming applications on multiprocessor systems-on-chips with predictable memory hierarchy. An iteration-based task-FIFO co-scheduling framework is proposed for this problem. We obtain FIFO size distributions using Pareto space searching, based on which the task-to-processor mapping is obtained with the potential FIFO allocation being taken into account; then, the FIFO-to-memory allocation is optimized to minimize the total memory access cost; finally, a self-timed throughput analysis method that considers memory and direct memory access controller contention is utilized to analyze the throughput. Our methods are validated by a set of synthesized and practical applications on different platforms

Task-FIFO co-scheduling of streaming applications on MPSoCs with predictable memory hierarchy

Multi-processor systems-on-chips are widely adopted in implementing modern streaming applications to satisfy the ever increasing computing requirements. Predictable memory hierarchies, which make memory access predictable, can better satisfy the strict timing requirements of streaming applications. However, different levels of the memory hierarchy vary in latency and capacity. Hence, the system performance not only depends on the task schedule but also closely relates with the FIFO size distribution and FIFO allocation, which makes the scheduling problem much more complex. We propose an efficient Iteration-based Task-FIFO Co-Scheduling algorithm to optimize the FIFO size distribution and task/FIFO assignment. Randomly generated Synchronous Dataflow Graphs with different sizes and a set of practical applications are used to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed algorithm outperforms the load balancing method and the Highest Access Frequency First algorithm

Task-FIFO co-scheduling of streaming applications on MPSoCs with predictable memory hierarchy

Multi-processor systems-on-chips are widely adopted in implementing modern streaming applications to satisfy the ever increasing computing requirements. Predictable memory hierarchies, which make memory access predictable, can better satisfy the strict timing requirements of streaming applications. However, different levels of the memory hierarchy vary in latency and capacity. Hence, the system performance not only depends on the task schedule but also closely relates with the FIFO size distribution and FIFO allocation, which makes the scheduling problem much more complex. We propose an efficient Iteration-based Task-FIFO Co-Scheduling algorithm to optimize the FIFO size distribution and task/FIFO assignment. Randomly generated Synchronous Dataflow Graphs with different sizes and a set of practical applications are used to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed algorithm outperforms the load balancing method and the Highest Access Frequency First algorithm