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Optimizing a Parallel Video Encoder with Message Passing and a Shared

Memory ArchitectureGU Junli

SUN Yihe

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Introduction & Related work Parallel encoder implementation Test results and Analysis Conclusions

Outline

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Parallel processing◦Real time

Parallel processing type◦Cluster[5], MPP[4]◦ Shared memory[6]

Introduction & Related work #1

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MPI (message passing interface)◦Communicate by passing message

Inefficient Shared memory◦ Share the same data space

Efficient

Introduction & Related work #2

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Most MPI codes adopt master-slave standard which has one master and couples of slaves to do different jobs.◦Workload imbalance◦Communication cost is high

On a typical shared memory CMP◦ Each code has a private L1 cache◦ Shared a large L2 cache

Introduction & Related work #3

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Balanced parallel scheme◦A strip-wise balanced parallel scheme

Parallel encoder implementation #1

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◦ Each process take one strip.◦ Each strip contains a number of slices

Sn = Frame_size/P◦ If Sn is not integer -> workload problem

Data dependency◦Message passing

Parallel encoder implementation #2

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Hybrid communication

Parallel encoder implementation #3

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Hybrid communication◦Combine MPI and shared memory

To reduce the communication cost◦ Ex. It takes 54.5ms to read a file and send the data to others

process by MPI but 9ms by shared memory. The memory allocation scheme has one global shared

memory area to store the original video data from where all processes read the original strip data.

Parallel encoder implementation #4

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Three dedicated memory spaces kept by each process including one for original data, a second for reconstructed data and the last for up-sampled data.

Parallel encoder implementation #5

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Environment◦ Two Intel Xeon E5310 @1.6 GHz processors, each with 4

cores. Test case◦HD, VGA, SD, CIF and QCIF

Version◦H264 JM10.2

Test results and Analysis #1

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Test results and Analysis #2

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25% higher speed improvement for the shared memory architecture as Compared to the case of cluster[5].

Test results and Analysis #3

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Test results and Analysis #4

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Test results and Analysis #5

0.2

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Test results and Analysis #6

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Test results and Analysis #7

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Test results and Analysis #8

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Test results and Analysis #9

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Upgrading legacy MPI applications to the class of shared memory architectures can provide significant performance improvements.

Optimizing the communication mechanism and further enhancements to the hybrid shared-memory and message-passing multi-core processor design can be expected to raise performance to still higher levels.

Conclusion #1