Parallelized benchmark-driven performance evaluation of SMPs and tiled multi-core architectures for embedded systems

With Moore's law supplying billions of transistors on-chip, embedded systems are undergoing a transition from single-core to multi-core to exploit this high transistor density for high performance. However, there exists a plethora of multi-core architectures and the suitability of these multi-core architectures for different embedded domains (e.g., distributed, real-time, reliability-constrained) requires investigation. Despite the diversity of embedded domains, one of the critical applications in many embedded domains (especially distributed embedded domains) is information fusion. Furthermore, many other applications consist of various kernels, such as Gaussian elimination (used in network coding), that dominate the execution time. In this paper, we evaluate two embedded systems multi-core architectural paradigms: symmetric multiprocessors (SMPs) and tiled multi-core architectures (TMAs). We base our evaluation on a parallelized information fusion application and benchmarks that are used as building blocks in applications for SMPs and TMAs. We compare and analyze the performance of an Intel-based SMP and Tilera's TILEPro64 TMA based on our parallelized benchmarks for the following performance metrics: runtime, speedup, efficiency, cost, scalability, and performance per watt. Results reveal that TMAs are more suitable for applications requiring integer manipulation of data with little communication between the parallelized tasks (e.g., information fusion) whereas SMPs are more suitable for applications with floating point computations and a large amount of communication between processor cores.