Objectives
This tutorial will introduce the audience to the BSC tools for heterogenous programming on FPGA devices. It describes OmpSs@FPGA, as a productive programming environment for compute systems with FPGAs.
More specifically, the tutorial will:
- Introduce the OmpSs@FPGA programming model, how to write, compile and execute applications on FPGAs
- Show the "implements" feature to explot parallelism across cores and IP cores
- Demonstrate how to analyze applications to determine which portions can be executed on FPGAs, and use OmpSs@FPGA to parallelize/optimize them.
Requirements
- Good knowledge of C/C++
- Basic knowledge of acceleration architectures and offloading models
- Basic knowledge of Paraver/Extrae
Please download and carefully read the following instructions regarding the logistics participants enrolling PATC at BSC are expected to follow.
Learning Outcomes
The students who finish this course will be able to develop benchmarks and simple applications with the OmpSs@FPGA programming model to be executed in FPGA boards, like Zedboard or Xilinx ZCU102.
Academic Staff
Convener: Xavier Martorell, CS/Programming Models
BSC - Computer Sciences department
Materials
INTELLECTUAL PROPERTY RIGHTS NOTICE:
• The User may only download, make and retain a copy of the materials for his/her use for non‐commercial and research purposes.
• The User may not commercially use the material, unless has been granted prior written consent by the Licensor to
do so; and cannot remove, obscure or modify copyright notices, text acknowledging or other means of identification or disclaimers as they appear.
• For further details, please contact BSC‐CNS patc [at] bsc [dot] es
Further information
All PATC Courses at BSC do not charge fees.
NOTE: PLEASE BRING YOUR OWN LAPTOP.
CONTACT US for further details about MSc, PhD, Post Doc studies, exchanges and collaboration in education and training with BSC.
For further details about Postgraduate Studies in UPC - Barcelona School of Informatics (FiB), visit the website.
Sponsors:
- BSC
- This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101083736.