2. numPYNQ - FPGA Rationale
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Numpynq is an efficient implementation of the NumPy library designed for PYNQ, aimed at processing large amounts of data to obtain aggregated information. The document compares the ease of use, performance, and flexibility of Numpynq with other processing systems like GPU, ASIC, CPU, and FPGA. Contact details for the authors are provided, along with links to their social media and slideshare.
2. numPYNQ - FPGA Rationale
- 1. numPYNQ Riccardo Pressiani riccardo.pressiani@mail.polimi.it Luca Stornaiuolo luca.stornaiuolo@mail.polimi.it Filippo Carloni filippo.carloni@mail.polimi.it FPGA Rationale
- 2. numPYNQ 2 Huge amount of data that need to be processed to get aggregated information
- 3. numPYNQ 3 Huge amount of data that need to be processed to get aggregated information
- 4. numPYNQ 4 Huge amount of data that need to be processed to get aggregated information Processing System
- 6. numPYNQ Comparison 6 Easiness of use Performance Flexibility GPU ASIC CPU FPGA
- 7. numPYNQ Comparison 7 Easiness of use Performance Flexibility GPU ASIC CPU FPGA
- 8. numPYNQ Comparison 8 Easiness of use Performance Flexibility GPU ASIC CPU
- 9. numPYNQ 9 Luca Stornaiuolo luca.stornaiuolo@mail.polimi.it Riccardo Pressiani riccardo.pressiani@mail.polimi.it Filippo Carloni filippo.carloni@mail.polimi.it Thanks for the attention!
- 10. numPYNQ an efficient implementationâš of the NumPy library for PYNQ https://twitter.com/numPYNQ_NECST https://www.facebook.com/numPYNQ https://www.slideshare.net/numPYNQ_at_NECST