3,107 research outputs found
Julia: A Fresh Approach to Numerical Computing
Bridging cultures that have often been distant, Julia combines expertise from
the diverse fields of computer science and computational science to create a
new approach to numerical computing. Julia is designed to be easy and fast.
Julia questions notions generally held as "laws of nature" by practitioners of
numerical computing:
1. High-level dynamic programs have to be slow.
2. One must prototype in one language and then rewrite in another language
for speed or deployment, and
3. There are parts of a system for the programmer, and other parts best left
untouched as they are built by the experts.
We introduce the Julia programming language and its design --- a dance
between specialization and abstraction. Specialization allows for custom
treatment. Multiple dispatch, a technique from computer science, picks the
right algorithm for the right circumstance. Abstraction, what good computation
is really about, recognizes what remains the same after differences are
stripped away. Abstractions in mathematics are captured as code through another
technique from computer science, generic programming.
Julia shows that one can have machine performance without sacrificing human
convenience.Comment: 37 page
Personalized Fuzzy Text Search Using Interest Prediction and Word Vectorization
In this paper we study the personalized text search problem. The keyword
based search method in conventional algorithms has a low efficiency in
understanding users' intention since the semantic meaning, user profile, user
interests are not always considered. Firstly, we propose a novel text search
algorithm using a inverse filtering mechanism that is very efficient for label
based item search. Secondly, we adopt the Bayesian network to implement the
user interest prediction for an improved personalized search. According to user
input, it searches the related items using keyword information, predicted user
interest. Thirdly, the word vectorization is used to discover potential targets
according to the semantic meaning. Experimental results show that the proposed
search engine has an improved efficiency and accuracy and it can operate on
embedded devices with very limited computational resources
CRAY mini manual. Revision D
This document briefly describes the use of the CRAY supercomputers that are an integral part of the Supercomputing Network Subsystem of the Central Scientific Computing Complex at LaRC. Features of the CRAY supercomputers are covered, including: FORTRAN, C, PASCAL, architectures of the CRAY-2 and CRAY Y-MP, the CRAY UNICOS environment, batch job submittal, debugging, performance analysis, parallel processing, utilities unique to CRAY, and documentation. The document is intended for all CRAY users as a ready reference to frequently asked questions and to more detailed information contained in the vendor manuals. It is appropriate for both the novice and the experienced user
The Scalable Brain Atlas: instant web-based access to public brain atlases and related content
The Scalable Brain Atlas (SBA) is a collection of web services that provide
unified access to a large collection of brain atlas templates for different
species. Its main component is an atlas viewer that displays brain atlas data
as a stack of slices in which stereotaxic coordinates and brain regions can be
selected. These are subsequently used to launch web queries to resources that
require coordinates or region names as input. It supports plugins which run
inside the viewer and respond when a new slice, coordinate or region is
selected. It contains 20 atlas templates in six species, and plugins to compute
coordinate transformations, display anatomical connectivity and fiducial
points, and retrieve properties, descriptions, definitions and 3d
reconstructions of brain regions. The ambition of SBA is to provide a unified
representation of all publicly available brain atlases directly in the web
browser, while remaining a responsive and light weight resource that
specializes in atlas comparisons, searches, coordinate transformations and
interactive displays.Comment: Rolf K\"otter sadly passed away on June 9th, 2010. He co-initiated
this project and played a crucial role in the design and quality assurance of
the Scalable Brain Atla
Evaluation of the SPAR thermal analyzer on the CYBER-203 computer
The use of the CYBER 203 vector computer for thermal analysis is investigated. Strengths of the CYBER 203 include the ability to perform, in vector mode using a 64 bit word, 50 million floating point operations per second (MFLOPS) for addition and subtraction, 25 MFLOPS for multiplication and 12.5 MFLOPS for division. The speed of scalar operation is comparable to that of a CDC 7600 and is some 2 to 3 times faster than Langley's CYBER 175s. The CYBER 203 has 1,048,576 64-bit words of real memory with an 80 nanosecond (nsec) access time. Memory is bit addressable and provides single error correction, double error detection (SECDED) capability. The virtual memory capability handles data in either 512 or 65,536 word pages. The machine has 256 registers with a 40 nsec access time. The weaknesses of the CYBER 203 include the amount of vector operation overhead and some data storage limitations. In vector operations there is a considerable amount of time before a single result is produced so that vector calculation speed is slower than scalar operation for short vectors
Space shuttle main engine numerical modeling code modifications and analysis
The user of computational fluid dynamics (CFD) codes must be concerned with the accuracy and efficiency of the codes if they are to be used for timely design and analysis of complicated three-dimensional fluid flow configurations. A brief discussion of how accuracy and efficiency effect the CFD solution process is given. A more detailed discussion of how efficiency can be enhanced by using a few Cray Research Inc. utilities to address vectorization is presented and these utilities are applied to a three-dimensional Navier-Stokes CFD code (INS3D)
Tupleware: Redefining Modern Analytics
There is a fundamental discrepancy between the targeted and actual users of
current analytics frameworks. Most systems are designed for the data and
infrastructure of the Googles and Facebooks of the world---petabytes of data
distributed across large cloud deployments consisting of thousands of cheap
commodity machines. Yet, the vast majority of users operate clusters ranging
from a few to a few dozen nodes, analyze relatively small datasets of up to a
few terabytes, and perform primarily compute-intensive operations. Targeting
these users fundamentally changes the way we should build analytics systems.
This paper describes the design of Tupleware, a new system specifically aimed
at the challenges faced by the typical user. Tupleware's architecture brings
together ideas from the database, compiler, and programming languages
communities to create a powerful end-to-end solution for data analysis. We
propose novel techniques that consider the data, computations, and hardware
together to achieve maximum performance on a case-by-case basis. Our
experimental evaluation quantifies the impact of our novel techniques and shows
orders of magnitude performance improvement over alternative systems
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Linking early geospatial documents, one place at a time: annotation of geographic documents with Recogito
Recogito is an open source tool for the semi-automatic annotation of place references in maps and texts. It was developed as part of the Pelagios 3 research project, which aims to build up a comprehensive directory of places referred to in early maps and geographic writing predating the year 1492. Pelagios 3 focuses specifically on sources from the Classical Latin, Greek and Byzantine periods; on Mappae Mundi and narrative texts from the European Medieval period; on Late Medieval Portolans; and on maps and texts from the early Islamic and early Chinese traditions. Since the start of the project in September 2013, the team has harvested more than 120,000 toponyms, manually verifying almost 60,000 of them. Furthermore, the team held two public annotation workshops supported through the Open Humanities Awards 2014. In these workshops, a mixed audience of students and academics of different backgrounds used Recogito to add several thousand contributions on each workshop day.
A number of benefits arise out of this work: on the one hand, the digital identification of places – and the names used for them – makes the documents' contents amenable to information retrieval technology, i.e. documents become more easily search- and discoverable to users than through conventional metadata-based search alone. On the other hand, the documents are opened up to new forms of re-use. For example, it becomes possible to “map” and compare the narrative of texts, and the contents of maps with modern day tools like Web maps and GIS; or to analyze and contrast documents’ geographic properties, toponymy and spatial relationships. Seen in a wider context, we argue that initiatives such as ours contribute to the growing ecosystem of the “Graph of Humanities Data” that is gathering pace in the Digital Humanities (linking data about people, places, events, canonical references, etc.), which has the potential to open up new avenues for computational and quantitative research in a variety of fields including History, Geography, Archaeology, Classics, Genealogy and Modern Languages
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