Given the decreasing cost of non-volatile RAM (NVRAM), by the late 1990’s it will be feasible for most workstations to include a megabyte or more of NVRAM, enabling the design of higher-performance, more reliable systems. We present the trace-driven simulation and analysis of two uses of NVRAM to improve I/O performance in distributed file systems: non-volatile file caches on client workstations to reduce write traffic to file servers, and write buffers for write-optimized file systems to reduce server disk accesses. Our results show that a megabyte of NVRAM on diskless clients reduces the amount of file data written to the server by 40 to 50%. Increasing the amount of NVRAM shows rapidly diminishing returns, and the particular NVRAM block replacement policy makes little difference to write traffic. Closely integrating the NVRAM with the volatile cache provides the best total traffic reduction. At today’s prices, volatile memory provides a better performance improvement per dollar than NVRAM for client caching, but as volatile cache sizes increase and NVRAM becomes cheaper, NVRAM will become cost effective. On the server side, providing a one-half megabyte write-buffer per file system reduces disk accesses by about 20 % on most of the measured logstructured file systems (LFS), and by 90 % on one heavilyused file system that includes transaction-processing workloads. 1.

A massively parallel processor proves to be a powerful tool for manipulating the very large Poisson series encountered in non-linear dynamics. Exploiting the algebraic structure of Poisson series leads quite naturally to parallel data structures and algorithms for symbolic manipulation. Exercising the parallel symbolic processor on the solution of Kepler's equation reveals the need to reexamine the serial computational methods traditionally applied to problems in dynamics.