Computer architecture

Programming language

Set (abstract data type)

Quantum

Physics

Multiplication (music)

Matrix multiplication

Acoustics

Quantum mechanics

Computer hardware

Integer (computer science)

Operating system

Systolic array

Parallel computing

Computer science

Process (computing)

Algorithm

Floating point

Computer engineering

FLOPS

Very-large-scale integration

Embedded system

Field-programmable gate array

While systolic array architectures have the potential to deliver tremendous performance, it is notoriously challenging to customize an efficient systolic array processor for a target application. Designing systolic arrays requires knowledge for both high-level characteristics of the application and low-level hardware details, thus making it a demanding and inefficient process. To relieve users from the manual iterative trial-and-error process, we present AutoSA, an end-to-end compilation framework for generating systolic arrays on FPGA. AutoSA is based on the polyhedral framework, and further incorporates a set of optimizations on different dimensions to boost performance. An efficient and comprehensive design space exploration is performed to search for high-performance designs. We have demonstrated AutoSA on a wide range of applications, on which AutoSA achieves high performance within a short amount of time. As an example, for matrix multiplication, AutoSA achieves 934 GFLOPs, 3.41 TOPs, and 6.95 TOPs in floating point, 16-bit and 8-bit integer data types on Xilinx Alveo U250.

AutoSA