The 30th Anniversary of the Supercomputing Conference: Bringing the Future Closer - Supercomputing History and the Immortality of Now

A panel of experts discusses historical reflections on the past 30 years of the Supercomputing (SC) conference, its leading role for the professional community and some exciting future challenges

The STAPL pList

We present the design and implementation of the Standard Template Adap- tive Parallel Library (stapl) pList, a parallel container that has the properties of a sequential list, but allows for scalable concurrent access when used in a paral- lel program. The stapl is a parallel programming library that extends C with support for parallelism. stapl provides a collection of distributed data structures (pContainers) and parallel algorithms (pAlgorithms) and a generic methodology for extending them to provide customized functionality. stapl pContainers are thread-safe, concurrent objects, providing appropriate interfaces (pViews) that can be used by generic pAlgorithms. The pList provides Standard Template Library (stl) equivalent methods, such as insert, erase, and splice, additional methods such as split, and efficient asyn- chronous (non-blocking) variants of some methods for improved parallel performance. List related algorithms such as list ranking, Euler Tour (ET), and its applications to compute tree based functions can be computed efficiently and expressed naturally using the pList. Lists are not usually considered useful in parallel algorithms because they do not allow random access to its elements. Instead, they access elements through a serializing traversal of the list. Our design of the pList, which consists of a collec- tion of distributed lists (base containers), provides almost random access to its base containers. The degree of parallelism supported can be tuned by setting the number of base containers. Thus, a key feature of the pList is that it offers the advantages of a classical list while enabling scalable parallelism. We evaluate the performance of the stapl pList on an IBM Power 5 cluster and on a CRAY XT4 massively parallel processing system. Although lists are generally not considered good data structures for parallel processing, we show that pList methods and pAlgorithms, and list related algorithms such as list ranking and ET technique operating on pLists provide good scalability on more than 16, 000 processors. We also show that the pList compares favorably with other dynamic data structures such as the pVector that explicitly support random access

Designing Practical Efficient Algorithms for Symmetric Multiprocessors

Symmetric multiprocessors (SMPs) dominate the high-end server market and are currently the primary candidate for constructing large scale multiprocessor systems. Yet, the design of efficient parallel algorithms for this platform currently poses several challenges. In this paper, we present a computational model for designing efficient algorithms for symmetric multiprocessors. We then use this model to create efficient solutions to two widely different types of problems - linked list prefix computations and generalized sorting. Our novel algorithm for prefix computations builds upon the sparse ruling set approach of Reid-Miller and Blelloch. Besides being somewhat simpler and requiring nearly half the number of memory accesses, we can bound our complexity with high probability instead of merely on average. Our algorithm for generalized sorting is a modification of our algorithm for sorting by regular sampling on distributed memory architectures. The algorithm is a stable sort which appears to be asymptotically faster than any of the published algorithms for SMPs. Both of our algorithms were implemented in C using POSIX threads and run on three symmetric multiprocessors - the DEC AlphaServer, the Silicon Graphics Power Challenge, and the HP-Convex Exemplar. We ran our code for each algorithm using a variety of benchmarks which we identified to examine the dependence of our algorithm on memory access patterns. In spite of the fact that the processors must compete for access to main memory, both algorithms still yielded scalable performance up to 16 processors, which was the largest platform available to us. For some problems, our prefix computation algorithm actually matched or exceeded the performance of the best sequential solution using only a single thread. Similarly, our generalized sorting algorithm always beat the performance of sequential merge sort by at least an order of magnitude, even with a single thread. (Also cross-referenced as UMIACS-TR-98-44

Quantitative performance modeling of scientific computations and creating locality in numerical algorithms

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 141-150) and index.by Sivan Avraham Toledo.Ph.D

Sixth Goddard Conference on Mass Storage Systems and Technologies Held in Cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems

This document contains copies of those technical papers received in time for publication prior to the Sixth Goddard Conference on Mass Storage Systems and Technologies which is being held in cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems at the University of Maryland-University College Inn and Conference Center March 23-26, 1998. As one of an ongoing series, this Conference continues to provide a forum for discussion of issues relevant to the management of large volumes of data. The Conference encourages all interested organizations to discuss long term mass storage requirements and experiences in fielding solutions. Emphasis is on current and future practical solutions addressing issues in data management, storage systems and media, data acquisition, long term retention of data, and data distribution. This year's discussion topics include architecture, tape optimization, new technology, performance, standards, site reports, vendor solutions. Tutorials will be available on shared file systems, file system backups, data mining, and the dynamics of obsolescence

Fifth NASA Goddard Conference on Mass Storage Systems and Technologies

This document contains copies of those technical papers received in time for publication prior to the Fifth Goddard Conference on Mass Storage Systems and Technologies held September 17 - 19, 1996, at the University of Maryland, University Conference Center in College Park, Maryland. As one of an ongoing series, this conference continues to serve as a unique medium for the exchange of information on topics relating to the ingestion and management of substantial amounts of data and the attendant problems involved. This year's discussion topics include storage architecture, database management, data distribution, file system performance and modeling, and optical recording technology. There will also be a paper on Application Programming Interfaces (API) for a Physical Volume Repository (PVR) defined in Version 5 of the Institute of Electrical and Electronics Engineers (IEEE) Reference Model (RM). In addition, there are papers on specific archives and storage products

Sensory Communication

Contains table of contents for Section 2, an introduction and reports on fourteen research projects.National Institutes of Health Grant RO1 DC00117National Institutes of Health Grant RO1 DC02032National Institutes of Health/National Institute on Deafness and Other Communication Disorders Grant R01 DC00126National Institutes of Health Grant R01 DC00270National Institutes of Health Contract N01 DC52107U.S. Navy - Office of Naval Research/Naval Air Warfare Center Contract N61339-95-K-0014U.S. Navy - Office of Naval Research/Naval Air Warfare Center Contract N61339-96-K-0003U.S. Navy - Office of Naval Research Grant N00014-96-1-0379U.S. Air Force - Office of Scientific Research Grant F49620-95-1-0176U.S. Air Force - Office of Scientific Research Grant F49620-96-1-0202U.S. Navy - Office of Naval Research Subcontract 40167U.S. Navy - Office of Naval Research/Naval Air Warfare Center Contract N61339-96-K-0002National Institutes of Health Grant R01-NS33778U.S. Navy - Office of Naval Research Grant N00014-92-J-184

NASA Tech Briefs, February 1995

No abstract availabl