1. Parallelizing Sobel Edge Detection Message-Passing, Shared-Memory, and Streaming Implementations Patrick Griffin, Levente Jakob, and James Psota

2. Methodology 3 Computational Models:  Message Passing  Shared Memory  Stream Evaluated on Raw simulator

3. Edges are defined by first derivative Find dx and dy with convolution Edge strength: We used: Sobel Edge Detection G y =G x =

4. Message Passing Implementation Calc Scatter + Calc Calc Gather + Calc Calc DRAM Tile8 distributes “oversized” partitions

5. Message Passing Results 177 cycles / pixel Memory copies kill performance  Packaging/unpackaging messages expensive  Alternative solution: send many messages, no need to package rMPI status  Seemingly correct, but currently not optimized  Non-blocking receives will help tremendously for some applications

6. Shared Memory Implementation

7. Shared Memory Results

8. Streaming Implementation Red Row Sum GxGx GyGy Green Row Sum GxGx GyGy Blue Row Sum GxGx GyGy PackSumAbs

9. Streaming Results 20 cycles / pixel Throughput limited by G x calculations Most nodes required no memory, G x and G y need 2 rows worth Integer ops + abs(float) All routing done on static network 1

10. Conclusions Streaming 4x slower than ideal Overhead of MP and SM detrimental MethodCycles / Pixel Ideal79/16 = 5 Streaming20 Shared Memory 539 Message Passing 177