38 research outputs found

    CRAY mini manual. Revision D

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    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

    Computerized Hittite Cuneiform Sign Recognition and Knowledge-Based System Application Examples

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    The Hittites had lived in Anatolia more than 4000 years ago. The Hittite language is one of the oldest and may be the only one still readable and grammar rules are known member of Indo-European language family. The Hittites had a cuneiform script of their own written on soft clay pads or tablets. Tablets made durable and permanent by baking them after writing with some tools. That is why they could endure for thousands of years buried in the ground. The study of Hittite language has been made manually on the Hittite cuneiform tablets. Unfortunately, field scientists have read and translated only a relatively small number of unearthed tablets. Many more tablets are still waiting under and over ground in Anatolia for reading and translation into various languages. To read and translate the cuneiform signs, using computeraided techniques would be a significant contribution not only to Anatolian and Turkish but also to human history. In this paper, recognition of Hittite cuneiform signs by using computer based image-processing techniques is reported. Additionally, uses of data-mining applications are also included in the paper. Most importantly, the authors also demonstrated feasibility of an expert system on the Hittite cuneiform script

    Fourth Conference on Artificial Intelligence for Space Applications

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    Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

    First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

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    Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered

    ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด ๋Ÿฐํƒ€์ž„์—์„œ์˜ ์‘์šฉํ”„๋กœ๊ทธ๋žจ ์‹œ์ž‘ ๊ฐ€์†์„ ์œ„ํ•œ ์ตœ์ ํ™”

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2015. 8. ๋ฌธ์ˆ˜๋ฌต.์ž๋ฐ”๋‚˜ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ์™€ ๊ฐ™์€ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋Ÿฐํƒ€์ž„ ํ™˜๊ฒฝ์€ ์‘์šฉํ”„๋กœ๊ทธ๋žจ์˜ ์ด์‹์„ฑ์„ ์žฅ์ ์œผ๋กœ ํ•˜์—ฌ ์ž„๋ฒ ๋””๋“œ ์†Œํ”„ํŠธ์›จ์–ด ํ”Œ๋žซํผ์œผ๋กœ์จ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ž๋ฐ” ์‘์šฉํ”„๋กœ๊ทธ๋žจ์€ ๋ฐ”์ดํŠธ์ฝ”๋“œ์˜ ํ˜•ํƒœ๋กœ ๋ฐฐํฌ๋˜์–ด ๋””์ง€ํ„ธ ํ…”๋ ˆ๋น„์ „์ด๋‚˜ ์•ˆ๋“œ๋กœ์ด๋“œ ํ”Œ๋žซํผ์—์„œ ๋™์ž‘ํ•˜๋ฉฐ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ๋Š” ์†Œ์Šค ์ฝ”๋“œ ํ˜•ํƒœ๋กœ ์›น ํ”Œ๋žซํผ์—์„œ ์ˆ˜ํ–‰๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด ๋Ÿฐํƒ€์ž„์— ์˜ํ•œ ์ด์‹์„ฑ์€ ๋ณธ์งˆ์ ์œผ๋กœ ์„ฑ๋Šฅ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•  ์ˆ˜ ์žˆ๋Š”๋ฐ, ํ•˜๋“œ์›จ์–ด๊ฐ€ ์•„๋‹Œ ์ธํ„ฐํ”„๋ฆฌํ„ฐ์™€ ๊ฐ™์€ ์†Œํ”„ํŠธ์›จ์–ด์— ์˜ํ•ด ์‘์šฉํ”„๋กœ๊ทธ๋žจ์˜ ๋ฐ”์ดํŠธ์ฝ”๋“œ๋‚˜ ์†Œ์Šค ์ฝ”๋“œ๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋” ๋‚˜์€ ์„ฑ๋Šฅ์„ ์–ป๊ธฐ ์œ„ํ•ด ์ˆ˜ํ–‰ ์ค‘ ๋ฐ”์ดํŠธ์ฝ”๋“œ๋‚˜ ์†Œ์Šค ์ฝ”๋“œ๋ฅผ ๊ธฐ๊ณ„์–ด๋กœ ๋ฒˆ์—ญํ•˜๋Š” ์ ์‹œ ์ปดํŒŒ์ผ๋Ÿฌ๋‚˜ inline caching๊ณผ ๊ฐ™์ด ๋ฐ˜๋ณต ์ˆ˜ํ–‰๋˜๋Š” ๋™์ž‘์— ํŠนํ™”๋œ ์ตœ์ ํ™”๋ฅผ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด ๋Ÿฐํƒ€์ž„์— ์ ์šฉํ•˜๊ธฐ๋„ ํ•œ๋‹ค. ํ•œํŽธ, ์ž„๋ฒ ๋””๋“œ ์‹œ์Šคํ…œ์—์„œ ๋™์ž‘ํ•˜๋Š” ์ž๋ฐ” ์‘์šฉํ”„๋กœ๊ทธ๋žจ์ด๋‚˜ ์›นํŽ˜์ด์ง€์˜ ๋กœ๋”ฉ ์ค‘ ์ˆ˜ํ–‰๋˜๋Š” ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ๋Š” ์•ˆ์ •๋œ ์ƒํƒœ์—์„œ์˜ ๋™์ž‘๋ณด๋‹ค๋Š” ๊ธ‰๊ฒฉํ•œ ๋ณ€ํ™”๋ฅผ ์ˆ˜๋ฐ˜ํ•˜๋Š” ์‹œ์ž‘ ๊ณผ์ •์˜ ํ–‰ํƒœ๊ฐ€ ๋” ๋‘๋“œ๋Ÿฌ์ง„๋‹ค. ๋”ฐ๋ผ์„œ ๋น„๊ต์  ์งง์€ ์ˆ˜ํ–‰์‹œ๊ฐ„์„ ๊ฐ€์ง€๊ณ , ๋™์ผํ•œ ๋™์ž‘์„ ๋ฐ˜๋ณตํ•˜๋Š” ๊ฒฝํ–ฅ์ด ๋‚ฎ์œผ๋ฉฐ, ์ˆ˜ํ–‰์‹œ๊ฐ„์—์„œ์˜ ๋น„์ค‘์ด ๋†’์€ ํ•ซ์ŠคํŒŸ์ด ๋“œ๋ฌธ ํŠน์ง•์„ ๊ฐ€์ง„๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•ซ์ŠคํŒŸ์— ํšจ๊ณผ์ ์ธ ์ ์‹œ ์ปดํŒŒ์ผ๋Ÿฌ๋‚˜ ๋ฐ˜๋ณต๋˜๋Š” ๋™์ž‘์— ํŠนํ™”๋œ ์ตœ์ ํ™”๋Š” ์ด์™€ ๊ฐ™์€ ์‘์šฉํ”„๋กœ๊ทธ๋žจ ์‹œ๋™์˜ ํ–‰ํƒœ์— ๋Œ€ํ•˜์—ฌ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์–ด๋ ค์šธ ์ˆ˜ ๋ฐ–์— ์—†๋‹ค. ์ด ๋…ผ๋ฌธ์„ ํ†ตํ•˜์—ฌ ๊ธฐ์กด์˜ ๋ฐฉ์‹ ๋ณด๋‹ค ์ •๊ตํ•˜๊ฒŒ ์ถ”์ •ํ•œ ์ˆ˜ํ–‰์‹œ๊ฐ„์„ ๊ทผ๊ฑฐ๋กœ ์ž‘๋™ํ•˜๋Š” ํ•ซ์ŠคํŒŸ ๊ฐ์ง€ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•จ์œผ๋กœ์จ ํ•ซ์ŠคํŒŸ์ด ๋ถˆ๋ถ„๋ช…ํ•œ ์ƒํ™ฉ์—์„œ ์ž๋ฐ” ์ ์‹œ ์ปดํŒŒ์ผ๋Ÿฌ์— ์˜ํ•œ ์ˆ˜ํ–‰ ์†๋„์˜ ํ–ฅ์ƒ์„ ๊พ€ํ•˜์—ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์‘์šฉํ”„๋กœ๊ทธ๋žจ ์‹œ์ž‘์˜ ํ–‰ํƒœ๋ฅผ ๋ณด์ด๋Š” ๋ฒค์น˜๋งˆํฌ ํ”„๋กœ๊ทธ๋žจ์˜ ์ฒซ๋ฒˆ์งธ ์ˆ˜ํ–‰์‹œ๊ฐ„์„ ๊ธฐ์กด์˜ HotSpot ์ž๋ฐ” ๊ฐ€์ƒ๋จธ์‹ ์˜ ํ•ซ์ŠคํŒŸ ๊ฐ์ง€ ๊ธฐ๋ฒ• ๋Œ€๋น„ ์•ฝ 10% ๊ฐ€์†ํ™”ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์‹ค์ œ ์‘์šฉํ”„๋กœ๊ทธ๋žจ์œผ๋กœ์„œ ๋””์ง€ํ„ธ ๋ฐฉ์†ก์— ์˜ํ•ด ๋ฐฐํฌ๋œ Xlet์˜ ์‹œ์ž‘์— ๊ฑธ๋ฆฌ๋Š” ์ˆ˜ํ–‰์‹œ๊ฐ„ ์—ญ์‹œ ์•ฝ 7%๊ฐ€ ๊ฐœ์„ ๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ ์ ์‹œ ์ปดํŒŒ์ผ๋Ÿฌ์—์„œ ์ƒ์„ฑ๋˜๋Š” ๊ธฐ๊ณ„์–ด์˜ ์šฉ๋Ÿ‰์„ ์ค„์ด๊ธฐ ์œ„ํ•˜์—ฌ ์ถ•์†Œ๋œ ๋ช…๋ น์–ด ์ง‘ํ•ฉ์— ์ตœ์ ํ™”๋œ ๊ธฐ๊ณ„์–ด๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์•ฝ 29%์— ํ•ด๋‹นํ•˜๋Š” ๊ธฐ๊ณ„์–ด์˜ ํฌ๊ธฐ๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ์—ˆ๊ณ , ์ด ๊ฒฐ๊ณผ๋Š” ์›นํŽ˜์ด์ง€ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ์˜ ์‹œ์ž‘ ๊ณผ์ •์—์„œ ์ˆ˜ํ–‰๋˜๋Š” ๋Œ€๋Ÿ‰์˜ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ์—์„œ ๋”์šฑ ํšจ๊ณผ์ ์ผ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ ์‹œ ์ปดํŒŒ์ผ๋Ÿฌ๋งŒ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ํ™˜๊ฒฝ์—์„œ ์›นํŽ˜์ด์ง€ ์ž๋ฐ”์Šคํฌ๋ฆผํŠธ ์‹œ์ž‘ ์†๋„์˜ ์„ฑ๋Šฅ ์ €ํ•˜๊ฐ€ ๋‚˜ํƒ€๋‚จ์„ ๋ฐœ๊ฒฌํ•˜์˜€๊ณ , ์ด๋ฅผ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ธํ„ฐํ”„๋ฆฌํ„ฐ ์ˆ˜ํ–‰์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์„ ํƒ์  ์ปดํŒŒ์ผ์„ ์‹œ๋„ํ•จ์œผ๋กœ์จ ์ ์‹œ ์ปดํŒŒ์ผ๋Ÿฌ์— ์˜ํ•œ ์„ฑ๋Šฅ ์ €ํ•˜๋ฅผ ์ตœ์†Œํ™” ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์›นํŽ˜์ด์ง€ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ ์‹œ์ž‘์˜ ์ˆ˜ํ–‰ ํ–‰ํƒœ์— ๋Œ€ํ•˜์—ฌ ๋ถ„์„์„ ์‹ค์‹œํ•œ ๊ฒฐ๊ณผ, ๋นˆ๋ฒˆํ•˜๊ฒŒ ๋ฐœ์ƒํ•˜๋Š” ๊ฐ์ฒด์— ๋Œ€ํ•œ ์ ‘๊ทผ์„ ๊ฐ€์†ํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐ”์ดํŠธ์ฝ”๋“œ ์ˆ˜์ค€์˜ ์ตœ์ ํ™”๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ธํ„ฐํ”„๋ฆฌํ„ฐ ์ˆ˜ํ–‰์— ์ ์‹œ ์ปดํŒŒ์ผ๋Ÿฌ๋ฅผ ์ถ”๊ฐ€๋กœ ์ ์šฉํ•˜์—ฌ๋„ ์›นํŽ˜์ด์ง€ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ ์‹œ์ž‘์˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ์€ ์—†์—ˆ๋˜ ๋ฐ˜๋ฉด, ์ œ์•ˆํ•œ ๋ฐ”์ดํŠธ์ฝ”๋“œ ์ˆ˜์ค€์˜ ์ตœ์ ํ™”๋Š” ์ˆ˜ํ–‰์‹œ๊ฐ„์„ ์•ฝ 3% ๊ฐ€์†ํ™”ํ•จ์œผ๋กœ์จ ์›นํŽ˜์ด์ง€ ์ž๋ฐ”์Šคํฌ๋ฆฝํŠธ ์‹œ์ž‘์— ๋” ํšจ๊ณผ์ ์ธ ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.Chapter 1. Introduction 1 1.1 Hot Spot Detection 1 1.2 Memory Consumption of JIT Compiled Code 4 1.3 Web Page JavaScript Performance with JITC 5 Chapter 2. Enhanced Hot Spot Detection 8 2.1 Previous Approaches to Hot Spot Detection 8 2.1.1 Simple Heuristic 8 2.1.2 Hot Heuristic 9 2.1.3 Static Analysis Heuristic 10 2.2 Flow-Sensitive Runtime Estimation 11 2.3 Static-FSRE for First-Invocation Compilation 15 2.4 Merged Heuristic of Dynamic and Static FSRE 18 2.4.1 Threshold of FSRE 18 2.4.2 Merged Heuristic 19 2.5 Experimental Results 19 2.5.1 Benchmark Results 19 2.5.1.1 Experimental Environment 19 2.5.1.2 Evaluation Heuristics 20 2.1.1.3 Performance of the Five Heuristics 21 2.1.1.4 Preciseness of Hot Spot Detection 23 2.1.1.5 Hot Spot Detection Time 28 2.1.1.6 Hot Spot Detection Overhead 29 2.5.2 Digital TV Java Xlet Results 31 2.5.2.1 DTV Environment and Java Xlet application 31 2.5.2.2 Heuristic Adjustments 33 2.5.2.3 Performance Improvement and Comparison 33 Chapter 3. Code Size Optimization for JITC 40 3.1 JavaScript JITC in SFX and Thumb2 40 3.1.1 JavaScript and Execution Semantics 40 3.1.2 SquirrelFish Extreme and the Bytecode 41 3.1.3 SFX JITC Architecture 43 3.1.4 JITC Code Generation for Thumb2 45 3.2 SFX JITC Optimizations for Thumb2 45 3.2.1 Code Generation with Register Re-map 45 3.2.2 Constant Pool Aggregation 46 3.2.3 Patching PC-relative Branches 49 3.3 Experimental Result 52 3.3.1 Experimental Environment 52 3.3.2 Code Size Result 52 3.3.3 Performance Result 55 Chapter 4. Selective JITC for Web Page JavaScript 56 4.1 JavaScript and SFX JITC 56 4.1.1 JavaScript and Interaction with DOM 56 4.1.2 SFX JITC and Its Architecture 59 4.1.3 Benchmark JavaScript and Web Page JavaScript 62 4.2 Selective JITC for the SFX 64 4.2.1 Selective JITC 64 4.2.2 Selective JITC Implementation for the SFX 65 4.3 Experimental Result 66 4.3.1 Experiment Environment 66 4.3.2 Web Page JavaScript and SunSpider Benchmark 66 4.3.3 Web page JavaScript Execution Time 71 4.3.4 Comparison to Benchmark Execution Time 73 4.3.5 Evaluation of the Selective JITC Heuristic 74 4.3.6 Discussions 76 Chapter 5. Bytecode Level Optimizations 78 5.1 Analysis on Web Page JavaScript Execution 78 5.2 Overhead in Property Accesses 82 5.3 Super-Bytecode Construction (SBC) 85 5.4 Bytecode Chaining (BC) 86 5.5 Experimental Evaluation 87 5.5.1 Performance Result 88 5.5.2 Performance Analysis 89 5.5.2.1 Optimized Runtime Services with SBC 89 5.5.2.2 Removed Runtime Services with BC 90 Chapter 6. Related Work 92 Chapter 7. Conclusion 94 Bibliography 97 Abstract 103Docto

    FY 1986 scientific and technical reports, articles, papers and presentations

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    Formal NASA technical reports, papers published in technical journals, and presentations by Marshall Space Flight Center (MSFC) personnel in FY-86 are presented. Also included are papers of MSFC contractors

    Models and evaluation of human-machine systems

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    "September 1993.""Prepared for: International Atomic Energy Association [sic], Wagramerstrasse 5, P. 0. Box 100 A-1400 Vienna, Austria."Part of appendix A and bibliography missingIncludes bibliographical referencesThe field of human-machine systems and human-machine interfaces is very multidisciplinary. We have to navigate between the knowledge waves brought by several areas of the human learning: cognitive psychology, artificial intelligence, philosophy, linguistics, ergonomy, control systems engineering, neurophysiology, sociology, computer sciences, among others. At the present moment, all these disciplines seek to be close each other to generate synergy. It is necessary to homogenize the different nomenclatures and to make that each one can benefit from the results and advances found in the other. Accidents like TMI, Chernobyl, Challenger, Bhopal, and others demonstrated that the human beings shall deal with complex systems that are created by the technological evolution more carefully. The great American writer Allan Bloom died recently wrote in his book 'The Closing of the American Mind' (1987) about the universities curriculum that are commonly separated in tight departments. This was a necessity of the industrial revolution that put emphasis in practical courses in order to graduate specialists in many fields. However, due the great complexity of our technological world, we feel the necessity to integrate again those disciplines that one day were separated to make possible their fast development. This Report is a modest trial to do this integration in a holistic way, trying to capture the best tendencies in those areas of the human learning mentioned in the first lines above. I expect that it can be useful to those professionals who, like me, would desire to build better human-machine systems in order to avoid those accidents also mentioned above

    Diseรฑo de controladores dedicados a la lรณgica difusa

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    Tesis doctoral inรฉdita. Universidad Autรณnoma de Madrid, Escuela Politรฉcnica Superior, Departamento de Ingenierรญa Informรกtica. Octubre de 2006Bibliograf.: p. 297-30
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