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Maximizing Acceleration in Data Processing: Migrating Applications to Maxeler

This document explores the potential for migrating applications to Maxeler technology, focusing on the types of applications best suited for this transition. It highlights critical factors such as execution time, particularly in loops, and the importance of high data reusability once data is moved to accelerators. The analysis includes expected acceleration benefits based on data characteristics and loop dependencies, providing insights for optimizing Big Data processing and enhancing application performance in hardware environments.

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Maximizing Acceleration in Data Processing: Migrating Applications to Maxeler

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  1. Maxeler Essence Revisited VeljkoMilutinovic and NenadKorolija

  2. Essence (1) • What applications are potentially migratable to Maxeler? • Extra long execution time. • Most of the execution time is in loops. • What loops to migrate? • High data reusability, once the data is moved to the accelerator. • High tolerance to long latencies, by the application. • What acceleration to expect? • If below the hardware limits,the more data,the higher the expected acceleration (good for Big Data) • The less sophisticated the data dependencies of different loop iterations, the higher the expected acceleration.

  3. Essence (2) FOR i = 1 2 3 4 5 … k … n DO FOR i = 1 2 3 4 5 … n DO T0 T1 T2 T3 T4 T0Tk T2k T3k OP1 OP1 OP2 OP2 OP3 OP3 OP4 OP4 OP5 OP5 OP6 OP6 . . . . . . OPkOPk Tk Tk+1 Tk+2 Tk T2k 1 result/clockMAX T3k T4k 1 result/k*clockCPU FPGA doing k operations CPU doing only one

  4. Essence (3) Hawaii Tahiti

  5. Essence (4)

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