This course aims to teach students the fundamentals of computing with FPGAs. By the end of the course, learners will understand why computing with FPGAs is important, be able to analyze the performance of FPGAs compared to microprocessors, and comprehend the benefits of stream architectures in saving power. The course covers topics such as Boolean Satisfiability, Content Addressable Memory, memory-like computation, VLSI CAD productivity, programming FPGAs, arithmetic for FPGAs, and encryption using the International Data Encryption Algorithm (IDEA). The teaching method involves lectures on various topics related to FPGAs, with a focus on practical examples and applications. This course is intended for individuals interested in hardware design, computer architecture, or FPGA programming.
Overview
Syllabus
Introduction.
Why Compute with FPGAS.
A Programmer's Technology Perspective.
Generic System Architecture.
Performance of FPGAS Examples.
Boolean Satisfiability.
BSAT FPGA versus Microprocessor.
Content Addressable Memory (CAM).
Memory-like Computation Example: Dynamic Graph Accelerator based on the Adjacency Matrix.
FPGAs versus DSP Processor International Data Encryption Algorithm (IDEA).
Stream Architecture Mapping a dataflow graph directly to the hardware.
Why Stream architectures save power.
Classification into Application Domains.
The VLSI CAD Productivity Gap.
Programming FPGAS #VLSI Synthesis.
The FPGA Programmers Task.
Adding Levels of Abstraction.
IDEA - Encryption.
What if there is a loop?.
Arithmetic for FPGAS.
Number Representation.
Precision / Range Optimization.
Arithmetic Styles.
Compound Arithmetic Example: Elementary Functions- undC math.
thoughts on syntax and semantics for programming FPGAS Syntax.
Conclusions.
Taught by
Stanford Online
