17 research outputs found

    Virtual synchronization for fast distributed cosimulation of dataflow task graphs

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    ๋งค๋‹ˆ์ฝ”์–ด ๊ฐ€์†๊ธฐ์˜ ๊ฒฐํ•จ์„ ๊ณ ๋ คํ•œ ํƒœ์Šคํฌ ๋งคํ•‘ ๋ฐ ์ž์› ๊ด€๋ฆฌ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2014. 8. ํ•˜์ˆœํšŒ.๊ธฐ์ˆ ์ด ๋ฐœ์ „ํ•จ์— ๋”ฐ๋ผ ํ•˜๋‚˜์˜ ์นฉ ์•ˆ์— ์ง‘์ ๋˜๋Š” ํ”„๋กœ์„ธ์„œ์˜ ๊ฐฏ์ˆ˜๊ฐ€ ์ ์  ์ฆ๊ฐ€ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ์‘์šฉ๋“ค์˜ ๋ณด๋‹ค ๋†’์€ ์—ฐ์‚ฐ ๋Šฅ๋ ฅ์— ๋Œ€ํ•œ ์š”๊ตฌ๋กœ ์ธํ•ด ๋งค๋‹ˆ์ฝ”์–ด ๊ฐ€์†๊ธฐ๋Š” ์‹œ์Šคํ…œ-์˜จ-์นฉ์—์„œ ์ค‘์š”ํ•œ ์—ฐ์‚ฐ ์žฅ์น˜๊ฐ€ ๋˜์—ˆ๋‹ค. ์‹œ์Šคํ…œ์˜ ์ƒํƒœ๊ฐ€ ์—ฌ๋Ÿฌ๊ฐ€์ง€ ์š”์ธ์— ์˜ํ•ด ๋™์ ์œผ๋กœ ๋ณ€ํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ์‹œ์Šคํ…œ ์ˆ˜ํ–‰์ค‘์— ๊ทธ๋Ÿฌํ•œ ๊ฐ€์†๊ธฐ๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ๋‹ค๋ฃจ๋Š” ๊ฒƒ์€ ๋งค์šฐ ์–ด๋ ค์šด ๋ฌธ์ œ์ด๋‹ค. ์‹œ์Šคํ…œ ์ˆ˜์ค€์—์„œ๋Š” ์‘์šฉ๋“ค์ด ์‚ฌ์šฉ์ž์˜ ์š”๊ตฌ์— ๋”ฐ๋ผ ์‹œ์ž‘ ๋˜๋Š” ์ข…๋ฃŒ๊ฐ€ ๋˜๊ณ , ์‘์šฉ ๋ ˆ๋ฒจ์—์„œ๋Š” ์‘์šฉ ์ž์ฒด์˜ ๋™์ž‘์ด ์ž…๋ ฅ ๋ฐ์ดํƒ€๋‚˜ ์ˆ˜ํ–‰๋ชจ๋“œ์— ๋”ฐ๋ผ ๋™์ ์œผ๋กœ ๋ณ€ํ•˜๊ฒŒ ๋œ๋‹ค. ์•„ํ‚คํ…์ฒ˜ ์ˆ˜์ค€์—์„œ๋Š” ํ”„๋กœ์„ธ์„œ์˜ ์˜๊ตฌ ๊ณ ์žฅ์œผ๋กœ ์ธํ•ด ํ•˜๋“œ์›จ์–ด ์ปดํฌ๋„ŒํŠธ์˜ ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ ์ƒํ™ฉ์ด ๋ณ€ํ•˜๊ฒŒ ๋œ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ๊ฐ€์†๊ธฐ๋ฅผ ๋‹ค๋ฃจ๋Š”๋ฐ ์žˆ์–ด์„œ์˜ ์œ„์™€ ๊ฐ™์€ ์–ด๋ ค์›€๋“ค์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์„ธ๊ฐ€์ง€ ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์ฒซ๋ฒˆ์งธ ๊ธฐ๋ฒ•์€ ํ”„๋กœ์„ธ์„œ์˜ ์˜๊ตฌ ๊ณ ์žฅ์ด ๋ฐœ์ƒํ•˜์˜€์„ ๋•Œ, ์ „์ฒด ์‘์šฉ๋“ค์„ ์‹œ๊ฐ„ ์ œ์•ฝ ํ•˜์— ์ฒ˜๋ฆฌ๋Ÿ‰์˜ ์ €ํ•˜๋ฅผ ์ตœ์†Œํ™”ํ•˜๋ฉฐ ์žฌ์Šค์ผ€์ฅด์„ ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ตœ์ ์˜ ์žฌ์Šค์ผ€์ฅด ๊ฒฐ๊ณผ๋“ค์€ ์ง„ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•˜์—ฌ ์ปดํŒŒ์ผ ์‹œ์—, ๊ฐ๊ฐ์˜ ํ”„๋กœ์„ธ์„œ ๊ณ ์žฅ ์ƒํ™ฉ์— ๋”ฐ๋ผ ์ค€๋น„๊ฐ€ ๋œ๋‹ค. ์ˆ˜ํ–‰ ์‹œ๊ฐ„์— ํ”„๋กœ์„ธ์„œ ๊ณ ์žฅ์ด ๊ฐ์ง€๋˜๋ฉด, ์ •์ƒ์ ์œผ๋กœ ๋™์ž‘ํ•˜๋Š” ํ”„๋กœ์„ธ์„œ๋“ค์ด ์ €์žฅ๋œ ์Šค์ผ€์ฅด์„ ๊ฐ€์ง€๊ณ  ํƒœ์Šคํฌ ์ด์ฃผ๋ฅผ ์ˆ˜ํ–‰ํ•œ ํ›„ ํƒœ์Šคํฌ๋“ค์˜ ๋‚˜๋จธ์ง€ ์ˆ˜ํ–‰์„ ์ง€์†ํ•œ๋‹ค. ์ด ๊ธฐ๋ฒ•์—์„œ๋Š” ๋˜ํ•œ ๋” ์ข‹์€ ์„ฑ๋Šฅ์„ ์–ป๊ธฐ ์œ„ํ•ด, ์„ ์ , ๋น„์„ ์  ๋ฐ ์œตํ•ฉ ์ด์ฃผ ์ •์ฑ…์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์˜ ๊ฐ€๋Šฅ์„ฑ์€ ์‹ค์ œ ๋””์ง€ํ„ธ ์‹ ํ˜ธ์ฒ˜๋ฆฌ ์‘์šฉ๋“ค๊ณผ ์ž„์˜๋กœ ์ƒ์„ฑ๋œ ์‘์šฉ๋“ค์— ๋Œ€ํ•ด ์‹œ๊ฐ„์ œ์•ฝ๊ณผ ๋‹ค์–‘ํ•œ ํ”„๋กœ์„ธ์„œ ๊ณ ์žฅ ์ƒํ™ฉ์— ๋Œ€ํ•ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ๋กœ ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ๋ณตํ•ฉ ์ž์› ๊ด€๋ฆฌ ๊ธฐ๋ฒ•์œผ๋กœ, ์ฒซ๋ฒˆ์งธ ๊ธฐ๋ฒ•์—์„œ ๋‹ค๋ฃฌ ํ”„๋กœ์„ธ์„œ ์˜๊ตฌ๊ณ ์žฅ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ๋™๊ธฐํ™” ๋ฐ์ดํƒ€-ํ๋ฆ„ ๊ทธ๋ž˜ํ”„๋กœ ๊ธฐ์ˆ ๋œ ์—ฌ๋Ÿฌ ์‘์šฉ๋“ค๊ณผ ์‘์šฉ๋“ค์˜ ๋™์  ์–‘์ƒ์„ ๋‹ค๋ฃจ๋Š” ๊ฒƒ๊นŒ์ง€๋กœ ํ™•์žฅ์ด ๋œ ๊ฒƒ์ด๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์—์„œ๋Š”, ์šฐ์„  ์„ค๊ณ„ ์ˆ˜์ค€์—์„œ ํ• ๋‹น๋˜๋Š” ํ”„๋กœ์„ธ์„œ์˜ ๊ฐฏ์ˆ˜๋ฅผ ๋ณ€ํ™”์‹œ์ผœ๊ฐ€๋ฉด์„œ ๋™๊ธฐํ™”๋œ ๋ฐ์ดํƒ€-ํ๋ฆ„ ๊ทธ๋ž˜ํ”„๋“ค์˜ ์ฒ˜๋ฆฌ๋Ÿ‰์ด ์ตœ๋Œ€๋กœ ์–ป์–ด์ง€๋Š” ๋งคํ•‘ ๊ฒฐ๊ณผ๋“ค์„ ์–ป๋Š”๋‹ค. ๊ทธ๋ฆฌ๊ณ ๋‚˜์„œ ์ˆ˜ํ–‰ ์‹œ๊ฐ„์—๋Š” ๋ฏธ๋ฆฌ ๊ณ„์‚ฐ๋œ ๋งคํ•‘ ์ •๋ณด๋“ค์„ ๊ฐ€์ง€๊ณ  ์ˆ˜ํ–‰์ค‘์ธ ์‘์šฉ๋“ค์˜ ๋งคํ•‘์„, ๋™์ ์ธ ์‹œ์Šคํ…œ ๋ณ€ํ™”๊ฐ€ ๋ฐœ์ƒํ•  ๋•Œ๋งˆ๋‹ค ์ ์šฉํ•˜๊ฒŒ ๋œ๋‹ค. ์ œ์•ˆ๋œ ์ž์› ๊ด€๋ฆฌ ๊ธฐ๋ฒ•์€ Noxim์ด๋ผ๋Š” ๋„คํŠธ์›Œํฌ-์˜จ-์นฉ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ ์œ„์—์„œ ๊ตฌํ˜„์ด ๋˜์—ˆ์œผ๋ฉฐ, ์‹คํ—˜ ๊ฒฐ๊ณผ๋“ค์€ ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์ด ์ตœ์‹ ์˜ ๋‹ค๋ฅธ ๊ธฐ๋ฒ•๋“ค๊ณผ ๋น„๊ตํ•˜์—ฌ ๋” ์ข‹์€ ์„ฑ๋Šฅ์„ ๋ณด์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ๋Š”, ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ์„ ์‹œ์Šคํ…œ-์˜จ-์นฉ ์ œ์ž‘ ์ด์ „์— ๋ณด๋‹ค ์ •ํ™•ํ•˜๊ฒŒ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด์„œ, ๋‘ ๋ฒˆ์งธ ๊ธฐ๋ฒ•์„ ๊ตฌํ˜„ํ•œ ์†Œํ”„ํŠธ์›จ์–ด ํ”Œ๋žซํผ์ด ๋งค๋‹ˆ์ฝ”์–ด ์•„ํ‚คํ…์ฒ˜๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ธฐ์กด์˜ ๋งค๋‹ˆ์ฝ”์–ด ์•„ํ‚คํ…์ฒ˜๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ์ƒ์œ„ ์ˆ˜์ค€์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ์„ฑ๋Šฅ์„ ์ธก์ •ํ•˜์˜€๊ธฐ ๋•Œ๋ฌธ์—, ์‹ค์ œ ์„ฑ๋Šฅ๊ณผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์„ฑ๋Šฅ์ด ์–ผ๋งˆ๋‚˜ ์ฐจ์ด๊ฐ€ ๋‚ ์ง€๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ์•Œ ์ˆ˜๊ฐ€ ์—†์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์†Œํ”„ํŠธ์›จ์–ด ํ”Œ๋žซํผ๊ณผ, ๊ฐ€์ƒ ํ”„๋กœํ† ํƒ€์ดํ•‘ ์‹œ์Šคํ…œ ๋ฐ ์ œ์˜จ ์—๋ฎฌ๋ ˆ์ด์…˜ ์‹œ์Šคํ…œ์—์„œ์˜ ํ”Œ๋žซํผ ๊ตฌํ˜„ ๋ฐฉ๋ฒ•์ด ์ œ์•ˆ์ด ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์‹ค์ œ ์‹œ์Šคํ…œ ๊ตฌํ˜„์„ ํ†ตํ•˜์—ฌ ์ œ์•ˆ๋œ ๋ณตํ•ฉ ์ž์› ๊ด€๋ฆฌ ๊ธฐ๋ฒ•์—์„œ์˜ ๋‹ค์–‘ํ•œ ๋™์  ๋น„์šฉ๋“ค์ด ์ •ํ™•ํ•˜๊ฒŒ ์ถ”์‚ฐ์ด ๋  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์‹คํ—˜์—์„œ๋Š” ์ œ์•ˆ๋œ ์†Œํ”„ํŠธ์›จ์–ด ๊ธฐ๋ฒ•์ด ํƒœ์Šคํฌ๋“ค์˜ ๋™์  ๋งคํ•‘๊ณผ ์ฒดํฌ-ํฌ์ธํŒ…์„ ํ†ตํ•œ ํ”„๋กœ์„ธ์„œ ์˜๊ตฌ ๊ณ ์žฅ์„ ํšจ๊ณผ์ ์œผ๋กœ ๊ฐ๋‚ดํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์˜€๋‹ค.Owing to the incessant technology improvement, the number of processors integrated into a single chip increases consistently, integrating more and more applications. Also, demand for higher computing capability for applications makes a many-core accelerator become an important computing resource in a system-on-chip. Efficient handling of the accelerator at run-time, however, is very challenging because the system status is subject to change dynamically by various factors. At the system level, the set of applications running concurrently may change according to user request. At the application level, the application behavior may change dynamically depending on input data or operation mode. At the architecture level, hardware resource availability may vary since hardware components may experience transient or permanent failures. In this thesis, to resolve the difficulties in handling many-core accelerator, three techniques are proposed. The first technique is the re-scheduling of the entire application to minimize throughput degradation under a latency constraint when a permanent processor failure occurs. Sub-optimal re-scheduling results using a genetic algorithm for each scenario of processor failures are obtained at compile-time. If a failure is detected at run-time, the live processors obtain the saved schedule, perform task transfer, and execute the remaining tasks of the current iteration. In this technique, preemptive and non-preemptive migration policies and a hybrid policy are proposed to obtain better performance. The viability of the proposed technique with real-life DSP applications as well as randomly generated graphs under timing constraints and random fault scenarios are shown through experiments. The second technique is a hybrid resource management scheme, expanded version of the first technique that also handles multi-applications specified as SDF graph and their relevant dynamisms such as application/task arrivals/ends as well as processor permanent failures. In the proposed technique, at design-time, throughput-maximized mappings of each SDF graph by varying the number of allocated processors are determined. Then, at run-time, the pre-computed mapping information is exploited to adjust the mapping of active applications to the processors without user intervention on the system status change. The proposed resource management is evaluated through intensive experiments with an in-house simulator built on top of Noxim, a Network-on-Chip simulator. Experimental results show the enhanced adaptability to dynamic system status change compared to other state-of-the-art approaches. Finally, the software platform for a homogeneous many-core architecture that implements the second technique is proposed to evaluate the system performance more accurately before SoC fabrication. Existing approaches usually use a high-level simulation model to estimate the performance without knowing how much actual performance will be deviated from the estimation. To overcome the limitation, the software platform is proposed and implementation details on a virtual prototyping system and on an emulation system realized with an Intel Xeon-Phi coprocessor are presented. Actual implementation enables us to investigate the overheads involved in the hybrid resource management technique in detail, which was not possible in high-level simulation. Experimental results confirm that the proposed software platform adapts to the dynamic workload variation effectively by dynamic mapping of tasks and tolerate unexpected core failures by check-pointing.Abstract i Contents iv List of Figures viii List of Tables xii Chapter 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . 1 1.2 Contribution . . . . . . . . . . . . 5 1.3 Thesis Organization . . . . . . . . . . . 7 Chapter 2 Preliminaries 8 2.1 Application Model . . . . . . . . . . 8 2.2 Architecture Model . . . . . . . . . . 13 2.3 Fault Model . . . . . . . . . . . . 15 2.4 Thesis Overview . . . . . . . . . . . 15 Chapter 3 Fault-aware Task Mapping 17 3.1 Introduction . . . . . . . . . . . . 17 3.2 Related Work . . . . . . . . . . . . 20 3.2.1 Static Approach . . . . . . . . . . 21 3.2.2 Dynamic Approach . . . . . . . . . . 22 3.3 Proposed Task Remapping/Rescheduling Technique . . 23 3.3.1 Remapping Technique . . . . . . . . 23 3.3.2 Rescheduling Technique . . . . . . . . 31 3.4 Experiments . . . . . . . . . . . . . 38 3.4.1 Remapping Results . . . . . . . . 38 3.4.2 Rescheduling Results . . . . . . . . 46 Chapter 4 Fault-aware Resource Management 53 4.1 Introduction . . . . . . . . . . . . 53 4.2 Related Work . . . . . . . . . . . . 54 4.2.1 Static Approach . . . . . . . . . . 55 4.2.2 Dynamic Approach . . . . . . . . . 55 4.2.3 Hybrid Approach . . . . . . . . . . 57 4.2.4 Summary . . . . . . . . . . . . 57 4.3 Background . . . . . . . . . . . . . 58 4.3.1 Energy Model . . . . . . . . . . . 59 4.3.2 Notation . . . . . . . . . . . . 60 4.4 Proposed Resource Management Technique . . . . 61 4.4.1 Motivational Example . . . . . . . . . 61 4.4.2 Overall Procedure . . . . . . . . . . 65 4.4.3 Design-time Analysis . . . . . . . . . 66 4.4.4 Run-time Mapping . . . . . . . . . . 67 4.5 Experiments . . . . . . . . . . . . . 74 4.5.1 Setup . . . . . . . . . . . . . . 74 4.5.2 Analysis of Run-time Overheads . . . . . . 75 4.5.3 Comparison with Other Approaches . . . . 79 Chapter 5 Software Platform for Resource Management 86 5.1 Introduction . . . . . . . . . . . . 86 5.2 Related Work . . . . . . . . . . . . 87 5.3 Overall Structure . . . . . . . . . . . . 88 5.4 Components of Software Platform . . . . . . 89 5.4.1 Application API Layer . . . . . . . . . 89 5.4.2 Communication Interface Module . . . . . 92 5.4.3 Host Interface Layer . . . . . . . . . 93 5.4.4 Memory Management Module . . . . . . 94 5.4.5 Design-time Analysis . . . . . . . . . 94 5.4.6 Slave Manager . . . . . . . . . . . 98 5.5 Software Platform Implementation . . . . . . 99 5.5.1 Scheduling Information . . . . . . . . 100 5.5.2 Function Migration and Execution . . . . . 101 5.5.3 Function Migration and Execution . . . . . 102 5.6 Virtual Prototyping System . . . . . . . . 105 5.7 Xeon Emulation System . . . . . . . . . 106 5.8 Experiments . . . . . . . . . . . . . 107 5.8.1 Setup . . . . . . . . . . . . . . 107 5.8.2 Experiments on the Virtual Prototyping System . . 108 5.8.3 Experiments on the Xeon Emulation System . . . 111 Chapter 6 Conclusion 116 Bibliography 119 Abstract in Korean 130Docto

    Optimierung der Energie und Power getriebenen Architekturexploration fรผr Multicore und heterogenes System on Chip

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    The contribution of this work builds on top of the established virtual prototype platforms to improve both SoC design quality and productivity. Initially, an automatic system-level power estimation framework was developed to address the critical issue of early power estimation in SoC design. The estimation framework models the static and dynamic power consumption of the hardware components. These models are created from the normalized values of the basic design components of SoC, obtained through one-time power simulation of RTL hardware models. The framework allows dynamic technology node reconfiguration for power estimation models. Its instantaneous power reporting aids the detection of possible hotspot early into the design process. Adding this additional data in conjunction with a steadily growing design space of complex heterogeneous SoC, finding the right parameter configuration is a challenging and laborious task for a system-level designer. This work addresses this bottleneck by optimizing the design space exploration (DSE) process for MPSoC design. An automatic DSE framework for virtual platforms (VPs) was developed which is flexible and allows the selection optimal parameter configuration without pre-existing knowledge. To reduce exploration time, the framework is equipped with several multi-objective optimization techniques based on simulated annealing and a genetic algorithm. Lastly, to aid HW/SW partitioning at system-level, a flexible and automated workflow (SW2TLM) is presented. It allows the designer to explore various possible partitioning scenarios without going into depth of the hardware architecture complexity and software integration. The framework generates system-level hardware accelerators from corresponding functionality encoded in the software code and integrates them into the VP. Power consumption and time speedups of acceleration is reported to the designer, which further increases the quality and productivity of the development process towards the final architecture. The presented tools are evaluated using a state-of-the-art VP for a range of single and multi-core applications. Viewing the energy delay product, a reduction in exploration time was recorded at approximately 62% (worst case), maintaining optimal parameter accuracy of 90% compared to previous techniques. While the SW2TLM further increases the exploration versatility by combining modern high-level synthesis with system-level architectural exploration.Der Beitrag dieser Arbeit baut auf dem etablierten Konzept der virtuellen Prototyp (VP) Plattformen auf, um die Qualitรคt und die Produktivitรคt des Entwurfsprozesses zu verbessern. Zunรคchst wurde ein automatisches System-Level-Framework entwickelt, um Verlustleistungsabschรคtzung fรผr SoC-Designs in einer deutlich frรผheren Entwicklungsphase zu ermรถglichen. Hierfรผr werden statischen und dynamischen Energieverbrauchsanteile individueller Hardwareelemente durch ein abstraktes Modell ausgedrรผckt. Das Framework ermรถglicht eine dynamische Anpassung des Technologieknotens sowie die Integration neuer Leistungsmodelle fรผr Drittanbieterkomponenten. Die kontinuierliche Erfassung der Energieverbrauchseigenschaften und ihre grafische Darstellung Benutzeroberflรคche unterstรผtzt zusรคtzlich die frรผhzeitige Identifikation mรถglicher Hotspots. Durch die Bereitstellung zusรคtzlicher Daten, in Verbindung mit einem stetig wachsenden Entwurfsraum komplexer SoCs, ist die Identifikation der richtigen Parameterkonfiguration eine zeitintensive Aufgabe. Die vorgelegten Konzepte erlauben eine gesteigerte Automatisierung des Explorationsprozesses. Techniken der mehrdimensionalen Optimierung, basierend auf Simulated Annealing und genetischer Algorithmen erlauben die Identifikation von geeigneten Konfigurationen ohne vorheriges Wissen oder Erfahrungswerte SchlieรŸlich wurde zur Unterstรผtzung der HW/SW -Partitionierung auf System-Ebene ein flexibler und automatisierter Workflow entwickelt. Er ermรถglicht es dem Designer verschiedene mรถgliche Partitionierungsszenarien zu untersuchen, ohne sich in die Komplexitรคt der Hardwarearchitektur und der Softwareintegration zu vertiefen. Das Framework erzeugt abstrakte Beschleunigermodelle aus entsprechenden Softwarefunktionen und integriert sie nahtlos in den ausfรผhrbare VP. Detaillierte Daten zum Energieverbrauch, Beschleunigungsfaktor und Kommunikationsoverhead der Partitionierung werden erfasst und dem Designer zur Verfรผgung gestellt, was die Qualitรคt und Produktivitรคt des weiter erhรถht. Die vorgestellten Tools werden mit einer modernen VP fรผr verschiedene SW-Anwendungen evaluiert. Bei Betrachtung des Energieverzรถgerungsprodukts wurde eine Verringerung der Explorationszeit um mehr als 62% bei 90% Parametergenauigkeit festgestell. Darauf aufbauend, erleichtert die automatisierte Untersuchung verschiedener HW/SW Partitionierungen die Entwicklung heterogener Architekturen durch die Kombination moderner HLS mit Architektur-Exploration auf der Systemebene

    Rapid Prototyping for Virtual Environments

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    Development of Virtual Environment (VE) applications is challenging where application developers are required to have expertise in the target VE technologies along with the problem domain expertise. New VE technologies impose a significant learning curve to even the most experienced VE developer. The proposed solution relies on synthesis to automate the migration of a VE application to a new unfamiliar VE platform/technology. To solve the problem, the Common Scene Definition Framework (CSDF) is developed, that serves as a superset/model representation of the target virtual world. Input modules are developed to populate the framework with the capabilities of the virtual world imported from VRML 2.0 and X3D formats. The synthesis capability is built into the framework to synthesize the virtual world into a subset of VRML 2.0, VRML 1.0, X3D, Java3D, JavaFX, JavaME, and OpenGL technologies, which may reside on different platforms. Interfaces are designed to keep the framework extensible to different and new VE formats/technologies. The framework demonstrated the ability to quickly synthesize a working prototype of the input virtual environment in different VE formats

    Performance analysis techniques for multi-soft-core and many-soft-core systems

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    Multi-soft-core systems are a viable and interesting solution for embedded systems that need a particular tradeoff between performance, flexibility and development speed. As the growing capacity allows it, many-soft-cores are also expected to have relevance to future embedded systems. As a consequence, parallel programming methods and tools will be necessarily embraced as a part of the full system development process. Performance analysis is an important part of the development process for parallel applications. It is usually mandatory when you want to get a desired performance or to verify that the system is meeting some real-time constraints. One of the usual techniques used by the HPC community is the postmortem analysis of application traces. However, this is not easily transported to the embedded systems based on FPGA due to the resource limitations of the platforms. We propose several techniques and some hardware architectural support to be able to generate traces on multiprocessor systems based on FPGAs and use them to optimize the performance of the running applications

    Modeling and Simulation in Engineering

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    This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results

    SoCRocket - A flexible and extensible Virtual Platform for the development of robust Embedded Systems

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    Der Schwerpunkt dieser Arbeit liegt in der Erhรถhung des Abstraktionsniveaus im Entwurfsprozess, speziell dem Entwurf von Systemen auf Basis von Virtuellen Plattformen (VPs), Transaction-Level-Modellierung (TLM) und SystemC. Es wird eine ganzheitliche Methode vorgestellt, mit der komplexe eingebettete Systeme effizient modelliert werden kรถnnen. Ergebnis ist eine der RTL-Synthese nahezu gleichgestellte Genauigkeit bei wesentlich hรถherer Flexibilitรคt und Simulationsgeschwindigkeit. Das SoCRocket-System orientiert sich dazu an existierenden Standards und stellt Methoden zu deren effizientem Einsatz zur Verbesserung von Simulationsgeschwindigkeit und Simulationsgenauigkeit vor. So wird unter anderem gezeigt, wie moderne Multi-Kanal-Protokolle mit Split-Transfers durch Ausgleich des Intertransaktions-Timings ohne die Einfรผhrung zusรคtzlicher Protokollphasen zeitlich genau modelliert werden kรถnnen. Standardisierungslรผcken in den Bereichen Speichermodellierung und Systemkonfiguration werden durch standardoffene Lรถsungen geschlossen. Darรผber hinaus wird neue Infrastruktur zur Modellierung von Signalkommunikation auf Transaktionsebene, der Verifikation von Komponenten und der Modellierung des Energieverbrauchs vorgestellt. Zur Demonstration wurden die Kernkomponenten einer im europรคischen Raumfahrtsektor maรŸgeblichen Hardwarebibliothek modelliert. Alle Komponenten wurden zunรคchst in Unit-Tests verifiziert und anschlieรŸend in einem Systemprototypen integriert. Zur Verifikation der Funktion, sowie Bestimmung von Simulationsgeschwindigkeit und zeitlicher Genauigkeit, wurde dieser fรผr unterschiedliche Abstraktionsstufen konfiguriert und mit einem in VHDL beschriebenen RISC-Referenzentwurf (LEON3MP) verglichen. Das System mit losem Timing (LT) und blockierender Kommunikation ist im Durchschnitt 561-mal schneller als die RTL-Referenz und weist eine durchschnittliche Timing-Abweichung von 7,04% auf. Das System mit nรคherungsweise akkuratem Timing (AT) und nicht-blockierender Kommunikation ist 335-mal schneller. Die durchschnittliche Timing-Abweichung betrรคgt hier nur noch 3,03%, was einer Standardabweichung von 0.033 und damit einer sehr hohen statistischen Sicherheit entspricht. Die verschiedenen Abstraktionsniveaus kรถnnen zur Realisierung mehrstufiger Architekturexplorationen eingesetzt werden. Dies wird am Beispiel einer hyperspektralen Bildkompression verdeutlicht.The focus of this work is raising the abstraction level in the development process, especially for the design of systems based on Virtual Platforms (VPs), Transaction Level Modeling (TLM), and SystemC. A holistic method for efficient modeling of complex embedded systems is presented. Results are accuracies close to RTL synthesis but at much higher flexibility, and simulation performance. The SoCRocket system integrates existing standards and introduces new methods for improvement of simulation performance and accuracy. It is shown, amongst others, how modern multi-channel protocols with split transfers can be accurately modeled by compensating inter-transaction timing without introducing additional protocol phases. Standardization gaps in the area of memory modeling and system configuration are closed by standard-open solutions. Furthermore, new infrastructure for modeling signal communication on transaction level, verification of components, and estimating power consumption are presented. All components have been verified in unit tests and were subsequently integrated in a system prototype. For functional verification, as well as measurement of simulation performance and accuracy, the prototype was configured for different abstractions and compared to a VHDL-based RISC reference design (LEON3MP). The loosely-timed platform prototype with blocking communication (LT) is in average 561 times faster than the RTL reference and shows an average timing deviation of 7,04%. The approximately-timed system (AT) with non-blocking communication is 335 times faster. Here, the timing deviation is only 3,03 %, corresponding to a standard deviation of 0.033, proving a very high statistic certainty. The systemโ€™s various abstraction levels can be exploited by a multi-stage architecture exploration. This is demonstrated by the example of a hyperspectral image compression

    A Co-Processor Approach for Efficient Java Execution in Embedded Systems

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    This thesis deals with a hardware accelerated Java virtual machine, named REALJava. The REALJava virtual machine is targeted for resource constrained embedded systems. The goal is to attain increased computational performance with reduced power consumption. While these objectives are often seen as trade-offs, in this context both of them can be attained simultaneously by using dedicated hardware. The target level of the computational performance of the REALJava virtual machine is initially set to be as fast as the currently available full custom ASIC Java processors. As a secondary goal all of the components of the virtual machine are designed so that the resulting system can be scaled to support multiple co-processor cores. The virtual machine is designed using the hardware/software co-design paradigm. The partitioning between the two domains is flexible, allowing customizations to the resulting system, for instance the floating point support can be omitted from the hardware in order to decrease the size of the co-processor core. The communication between the hardware and the software domains is encapsulated into modules. This allows the REALJava virtual machine to be easily integrated into any system, simply by redesigning the communication modules. Besides the virtual machine and the related co-processor architecture, several performance enhancing techniques are presented. These include techniques related to instruction folding, stack handling, method invocation, constant loading and control in time domain. The REALJava virtual machine is prototyped using three different FPGA platforms. The original pipeline structure is modified to suit the FPGA environment. The performance of the resulting Java virtual machine is evaluated against existing Java solutions in the embedded systems field. The results show that the goals are attained, both in terms of computational performance and power consumption. Especially the computational performance is evaluated thoroughly, and the results show that the REALJava is more than twice as fast as the fastest full custom ASIC Java processor. In addition to standard Java virtual machine benchmarks, several new Java applications are designed to both verify the results and broaden the spectrum of the tests.Siirretty Doriast
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