Stateful Dataflow Multigraphs: A Data-Centric Model for Performance Portability on Heterogeneous Architectures

02/27/2019
by   Tal Ben-Nun, et al.
0

The ubiquity of accelerators in high-performance computing has driven programming complexity beyond the skill-set of the average domain scientist. To maintain performance portability in the future, it is imperative to decouple architecture-specific programming paradigms from the underlying scientific computations. We present the Stateful DataFlow multiGraph (SDFG), a data-centric intermediate representation that enables separating program definition from its optimization. By combining fine-grained data dependencies with high-level control-flow, SDFGs are both expressive and amenable to program transformations, such as tiling and double-buffering. These transformations are applied to the SDFG in an interactive process, using extensible pattern matching, graph rewriting, and a graphical user interface. We demonstrate SDFGs on CPUs, GPUs, and FPGAs over various motifs — from fundamental computational kernels to graph analytics. We show that SDFGs deliver competitive performance, allowing domain scientists to develop applications naturally and port them to approach peak hardware performance without modifying the original scientific code.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 7

page 8

02/27/2019

Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs

With the ubiquity of accelerators, such as FPGAs and GPUs, the complexit...
12/22/2021

Lifting C Semantics for Dataflow Optimization

C is the lingua franca of programming and almost any device can be progr...
02/13/2021

COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry

The computational power increases over the past decades havegreatly enha...
05/05/2021

TENET: A Framework for Modeling Tensor Dataflow Based on Relation-centric Notation

Accelerating tensor applications on spatial architectures provides high ...
12/18/2019

A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations

The computational efficiency of a state of the art ab initio quantum tra...
10/20/2021

A Data-Centric Optimization Framework for Machine Learning

Rapid progress in deep learning is leading to a diverse set of quickly c...
05/19/2021

Pure Tensor Program Rewriting via Access Patterns (Representation Pearl)

Tensor kernels in machine learning (ML) often correspond to pure mathema...

Code Repositories

dace

DaCe - Data Centric Parallel Programming


view repo
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.