Developing FPGA - Accelerated cloud applications with SDAccel - Practice, Certificate | Part time online | Coursera | United States
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Developing FPGA - Accelerated cloud applications with SDAccel - Practice

1 months
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About

This Developing FPGA - Accelerated cloud applications with SDAccel - Practice course offered by Coursera in partnership with Politecnico di Milano is for anyone passionate about learning how to develop FPGA-accelerated applications with SDAccel!

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Overview

Key Features

The more general purpose you are, the more flexible you are and the more kinds of programs and algorithms you can execute on your underlying computing infrastructure. All of this is terrific, but there is no free food and this is happening, quite often, by losing inefficiency.

This Developing FPGA - Accelerated cloud applications with SDAccel - Practice course offered by Coursera in partnership with Politecnico di Milano will present several scenarios where the workloads require more performance than can be obtained even by using the fastest CPUs. This scenario is turning cloud and data center architectures toward accelerated computing. Within this course, we are going to show you how to gain benefits by using Xilinx SDAccel to program Amazon EC2 F1 instances. We are going to do this through a working example of an algorithm used in computational biology.

The huge amount of data the algorithms need to process and their complexity raised the problem of increasing the amount of computational power needed to perform the computation. In this scenario, hardware accelerators revealed to be effective in achieving a speed-up in the computation while, at the same time, saving power consumption. Among the algorithms used in computational biology, the Smith-Waterman algorithm is a dynamic programming algorithm, guaranteed to find the optimal local alignment between two strings that could be nucleotides or proteins. In the following classes, we present an analysis and successive FPGA-based hardware acceleration of the Smith-Waterman algorithm used to perform pairwise alignment of DNA sequences.

Within this context, this course is focusing on distributed, heterogeneous cloud infrastructures, providing you details on how to use Xilinx SDAccel, through working examples, to bring your solutions to life by using the Amazon EC2 F1 instances.

Programme Structure

Courses include:

  • Reconfigurable cloud infrastructure
  • On how to accelerate the cloud with SDAccel
  • Summing things up: the Smith-Waterman algorithm
  • The Smith-Waterman example in details
  • Course conclusions

Key information

Duration

  • Part-time
    • 1 months
    • 4 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • Intermediate Level
  • This course is aimed at students with prior programming experience and a desire to understand computation approaches to problem solving.
  • Tuition Fee

    To always see correct tuition fees
    • International

      Free
      Tuition Fee
      Based on the tuition of 0 USD for the full programme during 1 months.
    • National

      Free
      Tuition Fee
      Based on the tuition of 0 USD for the full programme during 1 months.

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    Funding

    Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved.

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