22,795 research outputs found
Architecture independent environment for developing engineering software on MIMD computers
Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management
Sail intelligent terminal evaluation
Engineering assessments, recommendations, and equipment necessary to solve the operational problems are described, and operational flexibility of the intelligent terminal facility are extended. The following capabilities were considered: (1) the operation of at least two D/D stations and one remote graphics terminal simultaneously; (2) the capability to run plotter, AIDS and FORTRAN programs simultaneously; (3) simultaneous use of system utility routines of D/D stations and remote graphics terminal; (4) the capability to provide large volume hardcopy of data and graphics; and (5) the capability to eliminate or at least ease the current operation/programming problems with related labor costs. The overall intelligent terminal development, and plans guiding the analysis and equipment acquisitions were studied, and the assessments and analyses performed are also summarized
On the Fly Orchestration of Unikernels: Tuning and Performance Evaluation of Virtual Infrastructure Managers
Network operators are facing significant challenges meeting the demand for
more bandwidth, agile infrastructures, innovative services, while keeping costs
low. Network Functions Virtualization (NFV) and Cloud Computing are emerging as
key trends of 5G network architectures, providing flexibility, fast
instantiation times, support of Commercial Off The Shelf hardware and
significant cost savings. NFV leverages Cloud Computing principles to move the
data-plane network functions from expensive, closed and proprietary hardware to
the so-called Virtual Network Functions (VNFs). In this paper we deal with the
management of virtual computing resources (Unikernels) for the execution of
VNFs. This functionality is performed by the Virtual Infrastructure Manager
(VIM) in the NFV MANagement and Orchestration (MANO) reference architecture. We
discuss the instantiation process of virtual resources and propose a generic
reference model, starting from the analysis of three open source VIMs, namely
OpenStack, Nomad and OpenVIM. We improve the aforementioned VIMs introducing
the support for special-purpose Unikernels and aiming at reducing the duration
of the instantiation process. We evaluate some performance aspects of the VIMs,
considering both stock and tuned versions. The VIM extensions and performance
evaluation tools are available under a liberal open source licence
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
A Survey on Array Storage, Query Languages, and Systems
Since scientific investigation is one of the most important providers of
massive amounts of ordered data, there is a renewed interest in array data
processing in the context of Big Data. To the best of our knowledge, a unified
resource that summarizes and analyzes array processing research over its long
existence is currently missing. In this survey, we provide a guide for past,
present, and future research in array processing. The survey is organized along
three main topics. Array storage discusses all the aspects related to array
partitioning into chunks. The identification of a reduced set of array
operators to form the foundation for an array query language is analyzed across
multiple such proposals. Lastly, we survey real systems for array processing.
The result is a thorough survey on array data storage and processing that
should be consulted by anyone interested in this research topic, independent of
experience level. The survey is not complete though. We greatly appreciate
pointers towards any work we might have forgotten to mention.Comment: 44 page
Influence of Input/output Operations on Processor Performance
Nowadays, computers are frequently equipped with peripherals that transfer great
amounts of data between them and the system memory using direct memory access
techniques (i.e., digital cameras, high speed networks, . . . ). Those peripherals prevent the
processor from accessing system memory for significant periods of time (i.e., while they
are communicating with system memory in order to send or receive data blocks). In this
paper we study the negative effects that I/O operations from computer peripherals have on
processor performance. With the help of a set of routines (SMPL) used to make discrete
event simulators, we have developed a configurable software that simulates a computer
processor and main memory as well as the I/O scenarios where the periph-erals operate.
This software has been used to analyze the performance of four different processors in four
I/O scenarios: video capture, video capture and playback, high speed network, and serial
transmission
Mission Control Center enhancement opportunities in the 1990's
The purpose of this paper is to present a framework for understanding the major enhancement opportunities for Air Force Mission Control Center/Test Support Centers (MCC's/TSC's) in the 1990's. Much of this paper is based on the findings of Study 232 and work currently underway in Study 2-6 for the Air Force Systems Command, Space System Division, Network Program Office. In this paper, we will address MCC/TSC enhancement needs primarily from the operator perspective, in terms of the increased capabilities required to improve space operations task performance
On-Disk Data Processing: Issues and Future Directions
In this paper, we present a survey of "on-disk" data processing (ODDP). ODDP,
which is a form of near-data processing, refers to the computing arrangement
where the secondary storage drives have the data processing capability.
Proposed ODDP schemes vary widely in terms of the data processing capability,
target applications, architecture and the kind of storage drive employed. Some
ODDP schemes provide only a specific but heavily used operation like sort
whereas some provide a full range of operations. Recently, with the advent of
Solid State Drives, powerful and extensive ODDP solutions have been proposed.
In this paper, we present a thorough review of architectures developed for
different on-disk processing approaches along with current and future
challenges and also identify the future directions which ODDP can take.Comment: 24 pages, 17 Figures, 3 Table
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