that are in a small file, hashing will likely save disk space and time. Hashing should be part of the tool kit of every programmer who deals with large files. Hashing is designed to allow a programmer to subset a large file, based on information in a small file (as is shown in figure 1). While

file system clusters data that is sequentially accessed and provides two block sizes to allow fast access to large files while not wasting large amounts of space for small files. File access rates of up to ten times faster than the traditional UNIX file system are experienced. Long needed enhancements

of simulations that demonstrate the efficiency of a simple cleaning policy based on cost and benefit. We have implemented a prototype logstructured file system called Sprite LFS; it outperforms current Unix file systems by an order of magnitude for small-file writes while matching or exceeding Unix performance

of records examined in each search is independent of the file size. The expected computation to perform each search is proportional-to 1ogN. Empirical evidence suggests that except for very small files, this algorithm is considerably faster than other methods.

, at the expense of other potential workloads. While some applications have adapted to I/O best practices and can obtain good performance on these systems, the natural I/O patterns of many applications result in generation of many small files. These applications are not well served by current parallel file systems

Small file performance in most file systems is limited by slowly improving disk access times, even though current file systems improve on-disk locality by allocating related data objects in the same general region. The key insight for why current file systems perform poorly is that locality

of available computers, communicating as appropriate through files, TCP pipes, and shared-memory FIFOs. The vertices provided by the application developer are quite simple and are usually written as sequential programs with no thread creation or locking. Concurrency arises from Dryad scheduling vertices to run

people's computers or share files in various (often ad hoc) ways. Nowadays some systems have many processors per user, either in the form of a parallel computer or a large collection of CPUs shared by a small user community. Such systems are usually called parallel or distributed computer systems

and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion

This paper proposes architectural refinements, server-driven metadata prefetching and namespace flattening, for improving the efficiency of small file workloads in object-based storage systems. Server-driven metadata prefetching consists of having the metadata server provide information