Concurrent DASSL Applied to Dynamic Distillation Column Simulation

The accurate, high-speed solution of systems of ordinary differential-algebraic equations (DAE’s) of low index is of great importance in chemical, electrical and other engineering disciplines. Petzold’s Fortran-based DASSL is the most widely used sequential code for solving DAE’s. We have devised and implemented a completely new C code, Concurrent DASSL, specifically for multicomputers and patterned on DASSL. In this work, we address the issues of data distribution and the performance of the overall algorithm, rather than just that of individual steps. Concurrent DASSL is designed as an open, application-independent environment below which linear algebra algorithms may be added in addition to standard support for dense and sparse algorithms. The user may furthermore attach explicit data interconversions between the main computational steps, or choose compromise distributions. A “problem formulator” (simulation layer) must be constructed above Concurrent DASSL, for any specific problem domain. We indicate performance for a particular chemical engineering application, a sequence of coupled distillation columns. Future efforts are cited in conclusion

A Portable Multicomputer Communication Library atop the Reactive Kernel

Sophisticated multicomputer applications require efficient, flexible, convenient underlying communication primitives. In the work described here, Zipcode, a new, portable communication library, has been designed, developed, articulated and evaluated. The primary goals were: high efficiency compared to lowest-level primitives, user-definable message receipt selectivity, as well as abstraction of collections of processes and message selectivity to allow multiple, independently conceived libraries to work together without conflict. Zipcode works atop the Caltech Reactive Kernel, a portable, minimalistic multicomputer node operating system. Presently, the Reactive Kernel is implemented for Intel iPSC/1, iPSC/2, and Symult s2010 multicomputers and emulated on shared-memory computers as well as networks of Sun workstations. Consequently, Zipcode addresses an equally wide audience, and can plausibly be run in other environments

LU Factorization of Sparse, Unsymmetric Jacobian Matrices on Multicomputers: Experience, Strategies, Performance

Efficient sparse linear algebra cannot be achieved as a straightforward extension of the dense case, even for concurrent implementations. This paper details a new, general-purpose unsymmetric sparse LU factorization code built on the philosophy of Harwell’s MA28, with variations. We apply this code in the framework of Jacobian-matrix factorizations, arising from Newton iterations in the solution of nonlinear systems of equations. Serious attention has been paid to the data-structure requirements, complexity issues and communication features of the algorithm. Key results include reduced communication pivoting for both the “analyze” A-mode and repeated B-mode factorizations, and effective general-purpose data distributions useful incrementally to trade-off process-column load balance in factorization against triangular solve performance. Future planned efforts are cited in conclusion

MPI Advance : Open-Source Message Passing Optimizations

The large variety of production implementations of the message passing interface (MPI) each provide unique and varying underlying algorithms. Each emerging supercomputer supports one or a small number of system MPI installations, tuned for the given architecture. Performance varies with MPI version, but application programmers are typically unable to achieve optimal performance with local MPI installations and therefore rely on whichever implementation is provided as a system install. This paper presents MPI Advance, a collection of libraries that sit on top of MPI, optimizing the underlying performance of any existing MPI library. The libraries provide optimizations for collectives, neighborhood collectives, partitioned communication, and GPU-aware communication.Comment: Available on conference website : https://eurompi23.github.io/assets/papers/EuroMPI23_paper_33.pd

Provenance Threat Modeling

Provenance systems are used to capture history metadata, applications include ownership attribution and determining the quality of a particular data set. Provenance systems are also used for debugging, process improvement, understanding data proof of ownership, certification of validity, etc. The provenance of data includes information about the processes and source data that leads to the current representation. In this paper we study the security risks provenance systems might be exposed to and recommend security solutions to better protect the provenance information.Comment: 4 pages, 1 figure, conferenc

A spectral estimation toolkit for Java applications

AbstractThis paper examines the capability, performance, and relevance of a high-performance advanced signal processing toolkit in Java, a programming language for Web-based applications. To demonstrate the simplicity, ease, and application use of the toolkit, a spectral estimation applet has been developed in the Java environment using advanced Internet technologies such as Remote Method Invocation (RMI). This application provides an interactive and visual approach in understanding theoretical concepts of advanced signal processing methods and shows the need to create more application applets to better understand additional concepts in signal and image processing. Furthermore, a toolkit with limited functionality and different framework has been developed for embedded and handheld devices such as cellular phones and palm pilots. This toolkit is also shown to be useful in developing applications MIDlets on those devices

An Overview of Cryptographic Accumulators

This paper is a primer on cryptographic accumulators and how to apply them practically. A cryptographic accumulator is a space- and time-efficient data structure used for set-membership tests. Since it is possible to represent any computational problem where the answer is yes or no as a set-membership problem, cryptographic accumulators are invaluable data structures in computer science and engineering. But, to the best of our knowledge, there is neither a concise survey comparing and contrasting various types of accumulators nor a guide for how to apply the most appropriate one for a given application. Therefore, we address that gap by describing cryptographic accumulators while presenting their fundamental and so-called optional properties. We discuss the effects of each property on the given accumulator's performance in terms of space and time complexity, as well as communication overhead.Comment: Note: This is an extended version of a paper published In Proceedings of the 7th International Conference on Information Systems Security and Privacy (ICISSP 2021), pages 661-66

Clustering Spam Domains and Destination Websites: Digital Forensics with Data Mining

Spam related cyber crimes have become a serious threat to society. Current spam research mainly aims to detect spam more effectively. We believe the identification and disruption of the supporting infrastructure used by spammers is a more effective way of stopping spam than filtering. The termination of spam hosts will greatly reduce the profit a spammer can generate and thwart his ability to send more spam. This research proposes an algorithm for clustering spam domains extracted from spam emails based on the hosting IP addresses and tracing the IP addresses over a period of time. The results show that many seemingly unrelated spam campaigns are actually related if the domain names in the URLs are investigated; spammers have a sophisticated mechanism for combating URL blacklisting by registering many new domain names every day and flushing out old domains; the domains are hosted at different IP addresses across several networks, mostly in China where legislation is not as tight as in the United States; old IP addresses are replaced by new ones from time to time, but still show strong correlation among them. This paper demonstrates an effective use of data mining to relate spam emails for the purpose of identifying the supporting infrastructure used for spamming and other cyber criminal activities

Collective-Optimized FFTs

This paper measures the impact of the various alltoallv methods. Results are analyzed within Beatnik, a Z-model solver that is bottlenecked by HeFFTe and representative of applications that rely on FFTs