Open-source high-level synthesis of tensorflow dataflow graphs using LegUp

A flow is presented for synthesizing Tensorflow computation graphs into FPGA accelerators using the open-source high-level synthesis (HLS) tool LegUp. The Tensorflow computation graph is represented translated from an intermediate representation in Tensorflow's Accelerated Linear Algebra (XLA) compiler called High Level Optimizer (HLO). This is translated into LLVM intermediate representation (IR) using a modified version of XLA's CPU backend. These modifications enable users to leverage IP modules for computation-intensive operations. For a simple instance of matrix multiply, using even a naively implemented IP is shown to give a 1.7x speedup over baseline accelerators synthesized from the original CPU backend.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Umenthum, Kenneth Richard

Contributors dc:contributor

• Chen, Deming

• tensorflow
• legup
• high level synthesis
• machine learning

Statement dc:rights

• Copyright 2019 Kenneth Richard Umenthum

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/104949

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/104949