90,390 research outputs found
Set processing in a network environment
A combination of a local network, a mass storage system, and an autonomous set processor serving as a data/storage management machine is described. Its characteristics include: content-accessible data bases usable from all connected devices; efficient storage/access of large data bases; simple and direct programming with data manipulation and storage management handled by the set processor; simple data base design and entry from source representation to set processor representation with no predefinition necessary; capability available for user sort/order specification; significant reduction in tape/disk pack storage and mounts; flexible environment that allows upgrading hardware/software configuration without causing major interruptions in service; minimal traffic on data communications network; and improved central memory usage on large processors
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COBOL report program generation by macro processor
The research described is directed towards the development of an interactive COBOL program generator. This aims to simplify computer usage and contribute to the more effective use of computer resources, by alleviating the burdensome, time-consuming and error-prone activity of programming.
The work is based on PG/1, an existing macro processor, and in particular considers the generation of report programs.
The problems of program generation by macro processor are first explored using Filetab, an existing report specification language,' and avoiding the interactive aspect. This establishes the feasibility of generating COBOL programs but identifies shortcomings in the macro processor facilities. Enhancements to the macro processor are defined and the PG/2 version is created
for use.
The development of an interactive self-instructional COBOL report program generator for the casual user is chosen as the area for deeper investigation.
From a consideration of data bases and query languages it is concluded that a relational view of the data forms the most natural basis for a computer-dominated, non-procedural report-specifying dialogue with a casual user.
A design study for an interactive self-teaching COBOL report program generator^ based on the PG/2 macro processor and offering some of the benefits of a Relational Data base Management System, is described. The validation of the user's responses is a major undertaking and leads to a large system. Details of the macros implementing selected features are presented.
It is concluded that program generation appears efficient but may be of even greater use to a professional programmer than to the non-specialist user. The PG/2 macro processor, although not an ideal tool for COBOL program generation, serves to identify the characteristics of an appropriate tool. There is potential for extending and adapting the techniques used to other applications
Expert System for UNIX System Reliability and Availability Enhancement
Highly reliable and available systems are critical to the airline industry. However, most off-the-shelf computer operating systems and hardware do not have built-in fault tolerant mechanisms, the UNIX workstation is one example. In this research effort, we have developed a rule-based Expert System (ES) to monitor, command, and control a UNIX workstation system with hot-standby redundancy. The ES on each workstation acts as an on-line system administrator to diagnose, report, correct, and prevent certain types of hardware and software failures. If a primary station is approaching failure, the ES coordinates the switch-over to a hot-standby secondary workstation. The goal is to discover and solve certain fatal problems early enough to prevent complete system failure from occurring and therefore to enhance system reliability and availability. Test results show that the ES can diagnose all targeted faulty scenarios and take desired actions in a consistent manner regardless of the sequence of the faults. The ES can perform designated system administration tasks about ten times faster than an experienced human operator. Compared with a single workstation system, our hot-standby redundancy system downtime is predicted to be reduced by more than 50 percent by using the ES to command and control the system
A Parallel Algorithm for Exact Bayesian Structure Discovery in Bayesian Networks
Exact Bayesian structure discovery in Bayesian networks requires exponential
time and space. Using dynamic programming (DP), the fastest known sequential
algorithm computes the exact posterior probabilities of structural features in
time and space, if the number of nodes (variables) in the
Bayesian network is and the in-degree (the number of parents) per node is
bounded by a constant . Here we present a parallel algorithm capable of
computing the exact posterior probabilities for all edges with optimal
parallel space efficiency and nearly optimal parallel time efficiency. That is,
if processors are used, the run-time reduces to
and the space usage becomes per
processor. Our algorithm is based the observation that the subproblems in the
sequential DP algorithm constitute a - hypercube. We take a delicate way
to coordinate the computation of correlated DP procedures such that large
amount of data exchange is suppressed. Further, we develop parallel techniques
for two variants of the well-known \emph{zeta transform}, which have
applications outside the context of Bayesian networks. We demonstrate the
capability of our algorithm on datasets with up to 33 variables and its
scalability on up to 2048 processors. We apply our algorithm to a biological
data set for discovering the yeast pheromone response pathways.Comment: 32 pages, 12 figure
ARM Wrestling with Big Data: A Study of Commodity ARM64 Server for Big Data Workloads
ARM processors have dominated the mobile device market in the last decade due
to their favorable computing to energy ratio. In this age of Cloud data centers
and Big Data analytics, the focus is increasingly on power efficient
processing, rather than just high throughput computing. ARM's first commodity
server-grade processor is the recent AMD A1100-series processor, based on a
64-bit ARM Cortex A57 architecture. In this paper, we study the performance and
energy efficiency of a server based on this ARM64 CPU, relative to a comparable
server running an AMD Opteron 3300-series x64 CPU, for Big Data workloads.
Specifically, we study these for Intel's HiBench suite of web, query and
machine learning benchmarks on Apache Hadoop v2.7 in a pseudo-distributed
setup, for data sizes up to files, web pages and tuples. Our
results show that the ARM64 server's runtime performance is comparable to the
x64 server for integer-based workloads like Sort and Hive queries, and only
lags behind for floating-point intensive benchmarks like PageRank, when they do
not exploit data parallelism adequately. We also see that the ARM64 server
takes the energy, and has an Energy Delay Product (EDP) that
is lower than the x64 server. These results hold promise for ARM64
data centers hosting Big Data workloads to reduce their operational costs,
while opening up opportunities for further analysis.Comment: Accepted for publication in the Proceedings of the 24th IEEE
International Conference on High Performance Computing, Data, and Analytics
(HiPC), 201
Asymptotic Analysis of Plausible Tree Hash Modes for SHA-3
Discussions about the choice of a tree hash mode of operation for a
standardization have recently been undertaken. It appears that a single tree
mode cannot address adequately all possible uses and specifications of a
system. In this paper, we review the tree modes which have been proposed, we
discuss their problems and propose remedies. We make the reasonable assumption
that communicating systems have different specifications and that software
applications are of different types (securing stored content or live-streamed
content). Finally, we propose new modes of operation that address the resource
usage problem for the three most representative categories of devices and we
analyse their asymptotic behavior
Semantic Compression for Edge-Assisted Systems
A novel semantic approach to data selection and compression is presented for
the dynamic adaptation of IoT data processing and transmission within "wireless
islands", where a set of sensing devices (sensors) are interconnected through
one-hop wireless links to a computational resource via a local access point.
The core of the proposed technique is a cooperative framework where local
classifiers at the mobile nodes are dynamically crafted and updated based on
the current state of the observed system, the global processing objective and
the characteristics of the sensors and data streams. The edge processor plays a
key role by establishing a link between content and operations within the
distributed system. The local classifiers are designed to filter the data
streams and provide only the needed information to the global classifier at the
edge processor, thus minimizing bandwidth usage. However, the better the
accuracy of these local classifiers, the larger the energy necessary to run
them at the individual sensors. A formulation of the optimization problem for
the dynamic construction of the classifiers under bandwidth and energy
constraints is proposed and demonstrated on a synthetic example.Comment: Presented at the Information Theory and Applications Workshop (ITA),
February 17, 201
Enhancing an Embedded Processor Core with a Cryptographic Unit for Performance and Security
We present a set of low-cost architectural enhancements to accelerate the execution of certain arithmetic operations common in cryptographic applications on an extensible embedded processor core. The proposed enhancements are generic in the sense that they can be beneficially applied in almost any RISC processor. We implemented the enhancements in form of a cryptographic unit (CU) that offers the programmer an extended instruction set. The CU features a 128-bit wide register file and datapath, which enables it to process 128-bit words and perform 128-bit loads/stores. We analyze the speed-up factors for some arithmetic operations and public-key cryptographic algorithms obtained through
these enhancements. In addition, we evaluate the hardware overhead (i.e. silicon area) of integrating the CU into an embedded RISC processor. Our experimental results show that the proposed architectural enhancements allow for a
significant performance gain for both RSA and ECC at the expense of an acceptable increase in silicon area. We also demonstrate that the proposed enhancements facilitate the protection of cryptographic algorithms against certain types of side-channel attacks and present an AES implementation
hardened against cache-based attacks as a case study
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