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Automated implementation of interface- and memory models for real-time video processing systems
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
2003 (English)In: Proceedings of IEEE Norchip Conference, November 2003 (Riga), 2003Conference paper, (Refereed)
Abstract [en]

We present a source-code generator for real-time video processing systems that automatically optimise the cache and scheduler performance for selected target architectures. Code can be directly generated from a modelled neighbourhood without any additional data dependency analysis. Experimental results show that almost all data cache misses are removed and we can see a reduction of the execution time in the order of 25 percent compared to non-tuned code. The source-code generator is a part of an automated and target independent development trajectory and motivated by improved designer productivity.

Place, publisher, year, edition, pages
2003.
Keyword [en]
real-time image processing, processor architecture
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-1831Local ID: 586OAI: oai:DiVA.org:miun-1831DiVA: diva2:26863
Available from: 2008-09-30 Created: 2008-09-30Bibliographically approved
In thesis
1. Memory modeling and synthesis for real-time video processing systems
Open this publication in new window or tab >>Memory modeling and synthesis for real-time video processing systems
2004 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mitthögskolan, 2004. 53 p.
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 4
Keyword
SystemC Memory Modeling and Synthesis
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-5680 (URN)2053 (Local ID)91-87908-84-0 (ISBN)2053 (Archive number)2053 (OAI)
Presentation
(English)
Available from: 2008-09-30 Created: 2009-07-10 Last updated: 2009-07-10Bibliographically approved
2. Memory modeling and synthesis for real-time video processing systems
Open this publication in new window or tab >>Memory modeling and synthesis for real-time video processing systems
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis, a new design methodology and new tools for modeling and synthesis of real-time video processing systems are presented. A real-time video processing system is a system that performs computations on a continuous sequence of images. Image processing is a memory intensive application. This, in turn, leads to the design challenge of bridging the classical gap of speed between memories and computational units. Several techniques exist for building memory hierarchies that exploit data- locality and reuse in order to overcome this memory gap. However, the support from tools to aid the designer in dataflow analysis and memory design is very modest. Additional constructs for modeling electronic systems enable well-known sequential programming languages such as C/C++ to be used for system modeling. Ocapi and SystemC, two object-oriented specification methods are compared in a case study. In this study, SystemC is found to be the most suitable specification method for video processing systems. Most operations invoked in video processing are neighborhood oriented. For a video system designer, this spatio-temporal collection of pixels represents a natural abstraction. In addition, the same pixel neighborhood reflects data dependencies that are crucial to system synthesis. An extended SystemC modeling methodology, called IMEM is presented. IMEM can be used to capture memory transactions and stream interfaces based on the pixel neighborhood as an abstraction. Two important steps towards synthesis of video systems onto Field Programmable Gate Arrays (FPGAs) are presented. These two steps are parts of a decomposition of the complete synthesis task. Firstly, the optimal sizes and placements of all FIFO-buffers in the memory system are optimized. Bit-widths, pipelining and possible sharing of FIFO-buffers among several data flow dependencies are considered at this step. Secondly, the set of FIFO-buffers are allocated onto a set of dual-ported fined grained memories. Both synthesis steps are formally modeled using network flow techniques and linear programming. In addition, a synthesis method that can automatically transform an IMEM model of a single spatial neighborhood into a multimedia processor implementation is presented. The cache and the instruction scheduler performance are both optimized by the tool. IMEM is an application specific methodology that provides the nonhardware skilled video designer with an easy programming model and an FPGA synthesis tool. Memory usage is modeled separately from computation. This is a key feature since memory usage is accepted as being the biggest design bottleneck for video processing.

Abstract [sv]

I denna avhandling presenteras en ny metod och nya verktyg för modellering och syntes av videobearbetande system i realtid. Ett videobearbetande system är ett system som utför beräkningar på en kontinuerlig ström av bilder. Bildbehandling är en minnesintensiv applikation. Detta i sin tur leder till en stor utmaning för konstruktören, nämligen att överbrygga en välkänd skillnad i hastighet mellan minnen och beräkningsenheter. Det finns ett flertal välkända tekniker att övervinna denna skillnad genom att utnyttja lokaliteten och återanvändningen av data. Stöd från befintliga verktyg som kan hjälpa konstruktören med dataflödesanalys och minneskonstruktion kan dock anses vara blygsam. Genom att tillföra mekanismer för modellering av elektroniska system, så kan traditionella sekventiella programmeringsspråk, så som C/C++ användas för modellering av system. Ocapi och SystemC är två objektorienterade specifikationsmetoder som jämförts i en fallstudie. I denna studie framstår SystemC som bäst lämpad för specifikation av videobearbetande system. De flesta bildbehandlingsoperationer arbetar på en lokal mängd av bildpunkter. För en bildbehandlingskonstruktör så framstår denna lokala mängd av bildpunkter som en abstraktion. Tillika representerar samma mängd bildpunkter de databeroenden som är avgörande vid syntes. I denna avhandling presenteras IMEM, en ny specifikationsmetod som kan användas till att modellera minnesanvänding och transaktioner genom att utnyttja en lokal mängd bildpunkter. Två betydelsefulla steg mot att med automatik kunna översätta en modell i IMEM till en implementation i en Field Programmable Gate Array (FPGA) beskrivs. Dessa två problemformuleringar är delsteg i hela syntesprocessen. I första steget optimeras placering och storlek av alla buffertminnen. Hänsyn tas härvid till bitbredd, pipelining och eventuell delning av buffertar mellan flera databeroenden. I det andra steget allokeras buffertminnen till en mängd små dubbelportade minnen. Båda syntesstegen modelleras formellt med hjälp av nätverksflöden och linjär programmering. Dessutom presenteras en syntesmetod som kan översätta en enkel IMEMmodell till en implementation i en mediaprocessor. Cache-minneshantering och schemaläggning av instruktioner optimeras av verktyget. IMEM är en applikationsspecifik metod för videosystem som tillhandahåller en enkel programmeringsmodell och ett syntesverktyg för FPGA-kretsar. Minnesanvändning modelleras separat från beräkningar. Detta är en viktig egenskap, eftersom i huvudsak minnestransaktionerna kommer att begränsa systemets prestanda.

Place, publisher, year, edition, pages
Sundsvall: Mittuniversitetet, 2006. 107 p.
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 8
Keyword
memory modeling
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-5883 (URN)4090 (Local ID)91-85317-19-5 (ISBN)4090 (Archive number)4090 (OAI)
Public defence
2006-05-18, O102, Sundsvall, 13:15 (English)
Opponent
Supervisors
Available from: 2008-09-30 Created: 2009-05-06 Last updated: 2011-02-06Bibliographically approved

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