Lifting C semantics for dataflow optimization


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Date

2022-06

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

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Rights / License

Abstract

C is the lingua franca of programming and almost any device can be programmed using C. However, programming modern heterogeneous architectures such as multi-core CPUs and GPUs requires explicitly expressing parallelism as well as device-specific properties such as memory hierarchies. The resulting code is often hard to understand, debug, and modify for different architectures. We propose to lift C programs to a parametric dataflow representation that lends itself to static data-centric analysis and enables automatic high-performance code generation. We separate writing code from optimizing for different hardware: simple, portable C source code is used to generate efficient specialized versions with a click of a button. Our approach can identify parallelism when no other compiler can, and outperforms a bespoke parallelized version of a scientific proxy application by up to 21%.

Publication status

published

Editor

Book title

ICS '22: Proceedings of the 36th ACM International Conference on Supercomputing

Journal / series

Volume

Pages / Article No.

17

Publisher

Association for Computing Machinery

Event

36th ACM International Conference on Supercomputing (ICS 2022)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Parallelism; Dataflow analysis; Automatic parallelization

Organisational unit

03950 - Hoefler, Torsten / Hoefler, Torsten check_circle

Notes

Funding

101034126 - Pilot using Independent Local & Open Technologies (EC)
101002047 - Productive Spatial Accelerator Programming (EC)
955776 - Network Solution for Exascale Architectures (EC)
955606 - DEEP- Software for Exascale Archtiectures (EC)

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