Developing FPGA-accelerated cloud applications with SDAccel: Practice

Topic outline

• Select topic Week 0 - Introduction to the course

  Week 0 - Introduction to the course

  
  Not available unless: You are a(n) Student
• Select topic Week 1 - Reconfigurable cloud infrastructure

  Week 1 - Reconfigurable cloud infrastructure

  

  Week 1 will talk about Distributed Systems, data center and cloud architectures, which are facing the exponential growth in computing requirements and the impossibility for CPU-based solutions to keep pace.

  Not available unless: You are a(n) Student
• Select topic Week 2 - On how to accelerate the cloud with SDAccel

  Week 2 - On how to accelerate the cloud with SDAccel

  

  Week 2 is going to have a first taste on how to gain the best out of the combination of the F1 instances with SDAccel providing some few practical instructions on how to develop accelerated applications on Amazon F1 by using the Xilinx SDAccel development environment. Then, we are going to present what it is necessary to create FPGA kernels, assemble the FPGA program and to compile the Amazon FPGA Image, or AFI. Finally, we will describe the steps and tasks involved in developing a host application accelerated on the F1 FPGA.

  Not available unless: You are a(n) Student
• Select topic Week 3 - Summing things up: the Smith_Waterman algorithm

  Week 3 - Summing things up: the Smith_Waterman algorithm

  

  Week 3 is going to introduce you to the Smith-Waterman algorithm that we have chosen to demonstrate how to create an hardware implementation of a system based on FPGA technologies using the Xilinx SDAccel design framework. We are going to dig into the details of the algorithm from its data structures to the computation flow. Then we are going to introduce the Roofline model and we are going to use it to analyze the theoretical peak performance and the operational intensity of the Smith-Waterman algorithm.

  Not available unless: You are a(n) Student
• Select topic Week 4 - The Smith-Waterman example in details

  Week 4 - The Smith-Waterman example in details

  

  Week 4 is going to dig deeper in the Smith-Waterman algorithm. We are going to implement a first version of the algorithm on a local server with the Xilinx SDAccel design framework. Then we are going to introduce some optimizations to improve performance, in particular we will add more parallelism in the implementation and we will introduce systolic arrays. Moreover, we will explore how we can perform data compression and then we will leverage multiple memory ports to improve memory access speed. Finally, we are going to port our implementation of the Smith-Waterman algorithm on the AWS F1 instances.

  Not available unless: You are a(n) Student
• Select topic Week 5 - Course conclusions

  Week 5 - Course conclusions

  

  Week 5 is concluding this course but posing interesting questions towards possible future research directions that may also point the students to other Coursera courses on FPGAs. We are working at the edge of the research in the area of reconfigurable computing. FPGA technologies are not used only as standalone solutions/platforms but are now included into cloud infrastructures. They are now used both to accelerate infrastructure/backend computations and exposed as-a-Service that can be used by anyone. Within this context we are facing the definition of new research opportunities and technology improvements and the time cannot be better under this perspective.

  Not available unless: You are a(n) Student
• Select topic Additional Resources

  Additional Resources