An explanation of the rationale behind the use of an FPGA-based system for our solution's implementation. A comparison is made between FPGAs, GPUs and ASICs.

1. 1
HAMSproject
Chiara Gatti
chiara1.gatti@mail.polimi.it
Guido Lanfranchi
guido2.lanfranchi@mail.polimi.it
2. FPGAs BECAUSE…
March, 17th 2016
NECST Lab, Politecnico di Milano
Credits: Shahriar Emil from the Noun Project

2. 2
The problem
If only MATLAB
simulations could
take less time…
https://thenounproject.com/

3. 3
The solution
If only MATLAB
simulations could
take less time…
https://thenounproject.com/
HARDWARE
ACCELERATION of
MATLAB
SIMULATIONS

4. 4
Hardware devices
GPUs
(Graphic Processing
Units)
ASICs
(Application Specific
Integrated Circuits)
FPGAs
(Field Programmable
Gate Arrays)

5. 5
Features
 Speedup vs GPPs
 Power requirements
 Flexibility
 Cost of the device

6. 6
Speedup (vs GPP[*]
)
GPUs
 High speedup
ASICs
 Best possible
FPGAs
 High speedup
[*]
General Purpose Processor

7. 7
Power requirements
GPUs
 High speedup
 Hundreds of watts
(Tesla K40 by Nvidia  max 235W)
ASICs
 Highest possible
 Lowest possible
FPGAs
 High speedup
 Tens of watts
(Virtex7-VC707 by Xilinx  abt 15W)

8. 8
Flexibility
GPUs
 High speedup
 Hundreds of watts
 Programmable
ASICs
 Highest possible
 Lowest possible
 Application-specific
FPGAs
 High speedup
 Tens of watts
 Programmable

9. 9
Costs
GPUs
 High speedup
 Hundreds of watts
 Programmable
 About 3000$ each
(Tesla K40 by Nvidia)
ASICs
 Highest possible
 Lowest possible
 Application-specific
 Too high if few
circuits required
FPGAs
 High speedup
 Tens of watts
 Programmable
 About 3500$ each
(Virtex7 VC707 by Xilinx)

10. 10
The choice
GPUs
 High speedup
 Hundreds of watts
 Programmable
 About 3000$ each
ASICs
 Highest possible
 Lowest possible
 Application-specific
 Too high if few
circuits required
FPGAs
 High speedup
 Tens of watts
 Programmable
 About 3500$ each

11. 11
The choice
GPUs
 High speedup
 Hundreds of watts
 Programmable
 About 3000$ each
ASICs
 Highest possible
 Lowest possible
 Application-specific
 Too high if few
circuits required
FPGAs
 High speedup
 Tens of watts
 Programmable
 About 3500$ each

12. 12
The choice
GPUs
 High speedup
 Hundreds of watts
 Programmable
 About 3000$ each
ASICs
 Highest possible
 Lowest possible
 Application-specific
 Too high if few
circuits required
FPGAs
 High speedup
 Tens of watts
 Programmable
 About 3500$ each

13. 13
The choice
GPUs
 High speedup
 Hundreds of watts
 Programmable
 About 3000$ each
FPGAs
 High speedup
 Tens of watts
 Programmable
 About 3500$ each

14. 14
The choice
GPUs
 High speedup
 Hundreds of watts
 Programmable
 About 3000$ each
FPGAs
 High speedup
 Tens of watts
 Programmable
 About 3500$ each

15. 15
The choice
FPGAs
 High speedup
 Tens of watts
 Programmable
 About 3500$ each

16. MATRIX INVERSION
16
First case study
• Intense computation
• Useful in different applications
(e.g. fluid dynamics lumped parameters model)
 reusability

17. MATRIX INVERSION
17
First case study
So… FPGAs!
- High speedup vs GPPs
- Low power requirements
- Programmable
- Affordable costs

18. ANY QUESTIONS?
HAMSprojectContact us!
You can find us…
hams.necst@gmail.com
chiara1.gatti@mail.polimi.it
guido2.lanfranchi@mail.polimi.it
www.facebook.com/hams.project
https://twitter.com/HAMS_project
http://www.slideshare.net/HAMSproject
https://vimeo.com/necstxohw16
https://www.youtube.com/channel/UCaovqRpUc7D_Uf2WJHL0rvA