numPYNQ @ NGCLE@e-Novia 15.11.2017

1. numPYNQ
Luca Stornaiuolo luca.stornaiuolo@polimi.it
Riccardo Pressiani riccardo.pressiani@mail.polimi.it
Filippo Carloni filippo.carloni@mail.polimi.it
15/11/2017
e-Novia
Sara Notargiacomo, Giuseppe Natale, Luca Cerina, Marco D. Santambrogio

2. numPYNQ
Context Definition
2
Huge amount of data that need to be processed to get aggregated information
Signal Processing Machine LearningData MiningImage Analysis

3. numPYNQ
Context Definition
3
GPUs are the most popular choice to
accelerate data analysis
Field Programmable Gate Array
(FPGA) are gaining momentum

4. numPYNQ
Context Definition
4
GPUs are the most popular choice to
accelerate data analysis
Field Programmable Gate Array
(FPGA) are gaining momentum
Performance
Energy
Efficiency
Flexibility Easy to Use
GPU
FPGA

5. numPYNQ 5
numPYNQ
numPYNQ is an FPGA-based hardware library that offers
data scientists an accelerated version of the core functions
of NumPy to be used transparently from their applications.
Performance
Energy
Efficiency
Flexibility Easy to Use
GPU
FPGA

6. numPYNQ 6
Overlay
Technology
Crosscorrelation
Matrix Dot Product

7. numPYNQ 7
Experimental Results

8. numPYNQ 8
Experimental Results

9. numPYNQ 9
Runtime Adaptivity
Runtime
Input Analysis
Target
Implementation

10. numPYNQ 10
Market
The Big Data market is estimated to top $61 billion in 2020,
a 26% compound annual growth rate for 2011-2020.
Source: Wikibon research as covered by KDNuggets.com

11. numPYNQ 11
Competition Analisys
numPYNQ
TensorFlow
PyCUDA

12. numPYNQ 12
Go to Market
Data Analysis-based
Companies
Partnership deal to complete the
development with the company support
Revenue sharing
Direct channel marketing through
sales force, email and online marketing
numPYNQ as a Service

13. numPYNQ 13
Freemium Model
Basic Plan Premium Plan Advanced Plan
Basic functions
Advanced Functions —
Dedicated Training —
Dedicated Support —
Custom Functions — —
Cost Free $ $$$

14. numPYNQ 14
Team
Luca Stornaiuolo
PhD student in Computer Science and Engineering at Politecnico di Milano
Role in numPYNQ project: Hardware Design and Optimization Manager
Riccardo Pressiani
MSc student in in Computer Science and Engineering at Politecnico di Milano
and University of Illinois at Chicago
Role in numPYNQ project: Hardware Implementation and Social Media Manager
Filippo Carloni
BSc student in Computer Science and Engineering at Politecnico di Milano
Role in numPYNQ project: PYNQ Overlay and Interfaces Manager
Sara Notargiacomo, Giuseppe Natale, Luca Cerina, Marco D. Santambrogio

15. numPYNQ
https://twitter.com/numPYNQ_NECST
https://www.facebook.com/numPYNQ
https://www.slideshare.net/numPYNQ_at_NECST
Thanks for the attention!