Informed prefetching of collective input/output requests

Optimizing collective input/output (I/O) is important for improving throughput of parallel scientific applications. Current research suggests that a specialized collective application programming interface, coupled with system-level optimizations, is necessary to obtain good I/O performance. Unfortunately, collective interfaces require an application to disclose its entire access pattern to fully reorder I/O requests, and cannot flexibly utilize additional memory to improve performance. In this paper we propose and analyze a method of optimizing collective access patterns using informed prefetching that is capable of exploiting any amount of available memory to overlap I/O with computation. We compare this approach to diskdirected I/O, an efficient implementation of a collective I/O interface. Moreover, we prove that under certain conditions, a per-processor prefetch depth equal to the number of drives can guarantee sequential disk accesses for any collectively accessed file. In empirical studies, a prefetch horizon of one to two times the number of disks per processor is sufficient to match the performance of disk-directed I/O for sequentially allocated files. Finally, we develop accurate analytical models to predict the throughput of informed prefetching for collective reads as a function of the per-processor prefetch depth.

A shared-disk parallel cluster file system

Dissertação apresentada para obtenção do Grau de Doutor em Informática Pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaToday, clusters are the de facto cost effective platform both for high performance computing (HPC) as well as IT environments. HPC and IT are quite different environments and differences include, among others, their choices on file systems and storage: HPC favours parallel file systems geared towards maximum I/O bandwidth, but which are not fully POSIX-compliant and were devised to run on top of (fault prone) partitioned storage; conversely, IT data centres favour both external disk arrays (to provide highly available storage) and POSIX compliant file systems, (either general purpose or shared-disk cluster file systems, CFSs). These specialised file systems do perform very well in their target environments provided that applications do not require some lateral features, e.g., no file locking on parallel file systems, and no high performance writes over cluster-wide shared files on CFSs. In brief, we can say that none of the above approaches solves the problem of providing high levels of reliability and performance to both worlds. Our pCFS proposal makes a contribution to change this situation: the rationale is to take advantage on the best of both – the reliability of cluster file systems and the high performance of parallel file systems. We don’t claim to provide the absolute best of each, but we aim at full POSIX compliance, a rich feature set, and levels of reliability and performance good enough for broad usage – e.g., traditional as well as HPC applications, support of clustered DBMS engines that may run over regular files, and video streaming. pCFS’ main ideas include: · Cooperative caching, a technique that has been used in file systems for distributed disks but, as far as we know, was never used either in SAN based cluster file systems or in parallel file systems. As a result, pCFS may use all infrastructures (LAN and SAN) to move data. · Fine-grain locking, whereby processes running across distinct nodes may define nonoverlapping byte-range regions in a file (instead of the whole file) and access them in parallel, reading and writing over those regions at the infrastructure’s full speed (provided that no major metadata changes are required). A prototype was built on top of GFS (a Red Hat shared disk CFS): GFS’ kernel code was slightly modified, and two kernel modules and a user-level daemon were added. In the prototype, fine grain locking is fully implemented and a cluster-wide coherent cache is maintained through data (page fragments) movement over the LAN. Our benchmarks for non-overlapping writers over a single file shared among processes running on different nodes show that pCFS’ bandwidth is 2 times greater than NFS’ while being comparable to that of the Parallel Virtual File System (PVFS), both requiring about 10 times more CPU. And pCFS’ bandwidth also surpasses GFS’ (600 times for small record sizes, e.g., 4 KB, decreasing down to 2 times for large record sizes, e.g., 4 MB), at about the same CPU usage.Lusitania, Companhia de Seguros S.A, Programa IBM Shared University Research (SUR