Optimizing data locality for SCI-based PC-clusters with the SMiLE monitoring approach

Modern low-latency and high-bandwidth interconnects like the Scalable Coherent Interface (SCI) deliver high communication performance for parallel and distributed systems. However, the performance of an SCI-based compute cluster with NUMA characteristics depends on the efficient use of local memory accesses. Therefore, programming and tool environments for such systems with distributed shared memory (DSM) should enable and exploit data locality. We present an event-driven hybrid monitoring approach for a SCI-based PC cluster with hardware supported DSM. The core of that concept is a hardware monitor which is able to observe the fine-grained nature of the communication in such a parallel system with minimal impact to the system. The hardware monitor delivers in real-time detailed information about the communication and runtime of an examined program. The monitoring system allows the user an optimal evaluation of the network behaviour and hence of the data locality of that parallel program