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Multiprocessor Architecture for Image processing

Multiprocessor Architecture for Image processing. Under the guidance of Dr.Anshul Kumar. Mayank Kumar – 2006EE10331 Pushpendre Rastogi – 2006EE50412. Objectives. To learn to work on FPGA platform. Learning the design philosophy of a soft core multiprocessor architecture.

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Multiprocessor Architecture for Image processing

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  1. Multiprocessor Architecture for Image processing Under the guidance of Dr.Anshul Kumar Mayank Kumar – 2006EE10331 Pushpendre Rastogi – 2006EE50412

  2. Objectives • To learn to work on FPGA platform. • Learning the design philosophy of a soft core multiprocessor architecture. • Using multiprocessor architecture to implement adaptive background mixture model for motion segmentation.i.e Background modeling and change detection algorithm. (Cris stauffer)

  3. Motivation • Signal processing, especially Image processing involves repetitive computation which can easily be divided into parallel computations • There are many algorithm that follows “locally sequential globally parallel” computation. • Surveillance camera related processing need economic real time solutions. • FPGA provides an easy way to alter design depending on algorithm requirements – making soft multicore processing feasible. • Architecture of the Processing Elements (PE) could be optimized for image processing.

  4. Adaptive background mixture model • The algorithm helps to generate an adaptive model for the background and helps in motion detection. • This can be applied for surveillance. • The algorithm is spatially parallel, thus computations for different part of the image can be done simultaneously. • This will help in real time operation of this algorithm on embedded platform.

  5. Nature of parallelism • Data Partitioning: The task is partitioned so that each processor performs exactly the same function, but on different sub-blocks of data. • For different image regions, our chosen algorithm is sequential in nature, which can be efficiently implemented through a processor.

  6. Basic Idea RGB Conversion Power PC M1 M1 M1 M E M O R Y Video DAC Video ADC` MPMC M1 M1 M1 M1 M1 M1 Array Topology Camera Monitor Virtex II Pro

  7. Basic Idea RGB Conversion Power PC M1 M1 M1 M E M O R Y Video DAC Video ADC` MPMC M1 M1 M1 M1 M1 M1 Array Topology Monitor Camera Virtex II Pro

  8. Inter-processor Communication [12] • For transferring large chunks of image data, we will be using shared external DDR Ram as • It provides large memory space for storing multiple frames. • Multiple processors can access the RAM simultaneously using MPMC. • For sharing intermediate computation results we will use FSL Links between neighboring processors. • Unidirectional point-to-point communication. • Unshared non-arbitrated communication mechanism. • FIFO based communication.

  9. Network Topology [1] • Completely meshed: Each node is connected to all other nodes. Adv: Reduce inter processor communication time. Disadvantage: Max 9 processors possible. • Ring Network: • Star Network • Array Network: (our choice)

  10. Overall Plan • Analysis of the algorithm. • Configuring Video input and output for XUPV2P FPGA kit. • Finalizing the architecture • For one processor • For two processors • For multiprocessors • Implementing • Basic Test algorithm • The algorithm

  11. Work Done • Studied Background mixture Model for foreground subtraction algorithm [2], [3], as a case study. • Analysis of the algorithm for: • Parallelism exploitation • Length of code for implementation • Memory requirements to store data. • Feasibility

  12. Work Done RGB Conversion Power PC Virtex II Pro Video DAC Video ADC` Monitor Camera Top Down Approach

  13. Work Done • Studied Microblaze architecture. [4] • Studied • FSL Link [5] • PLB, LMB, OPB Buses [6] • XPS Design Flow [7] • Literary survey on related works [8],[9], [10], [11] • Configuration Video input and output for XUPV2P FPGA kit. Bottom Up Approach

  14. Work Ahead – Step 1 RGB Conversion Power PC M E M O R Y Video DAC Memory Read And Write Video ADC` MPMC Camera Monitor Virtex II Pro 23rd Feb – 7th March

  15. Work Ahead – Step 2 RGB Conversion Power PC M E M O R Y Some Simple Processing Video DAC M1 Video ADC` MPMC Camera Monitor Virtex II Pro 8th March – 15th March

  16. Work Ahead – Step 3 RGB Conversion Power PC M1 M1 M1 M E M O R Y Video DAC Video ADC` MPMC M1 M1 M1 M1 M1 M1 Simple processing Camera Monitor Virtex II Pro 24th March – 5th April

  17. Work Ahead – Step 4 RGB Conversion Power PC M1 M1 M1 M E M O R Y Video DAC Video ADC` MPMC M1 M1 M1 M1 M1 M1 Complex Processing Camera Monitor Virtex II Pro 6th April – 19th April

  18. Time Line • Step 1 – 23rd Feb – 7th March • Step 2 – 8th March – 15th March • Step 3 – 24th March – 5th April • Step 4 – 6th April – 19th April

  19. Related Works • Design Development and performance evaluation of multiprocessor system on FPGA. Somen Barma, CSE IITD. [8]. • A Microblaze based Multiprocessor SoC[1] • An FPGA based soft multiprocessor system for IPv4 packet forwarding. [9] • An automated framework for FPGA based soft Multiprocessor System. [10] • Multiprocessor interconnection based on DMA for FPGA.[11]

  20. REFERENCES [1] A Microblaze based Multiprocessor SOC – 2003 [2] Adaptive background mixture model for real-time tracking – 1999 [3] Understanding background mixture model for foreground segmentation – 2002 [4] Microblaze processor reference guide [5] Xilinx FSL datasheet [6] Xilinx Microblaze bus interface (ppt) [7] Virtex II Pro design flow – getting started [8] Design Development and performance evaluation of multiprocessor system on FPGA. Somen Barma, CSE IITD. Under Prof Kolin Paul [9] An FPGA based soft multiprocessor system for IPv4 packet forwarding. [10] An automated framework for FPGA based soft Multiprocessor System. [11] Multiprocessor interconnection based on DMA for FPGA. [12] XPS White paper – Designing multiprocessor System on Platform Stdio. Visit www.cse.iiitd.ernet.in/~ee5060412

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