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Compound memory models

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Goens_2023_PAPL_Compound_memory_CC.pdf (349.0Kb)
Date
06/06/2023
Author
Goens, Andrés
Chakraborty, Soham
Sarkar, Susmit
Agarwal, Sukarn
Oswald, Nicolai
Nagarajan, Vijay
Keywords
Compound memory models
Consistency models
Coherence protocols
QA75 Electronic computers. Computer science
DAS
MCC
NCAD
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Abstract
Today’s mobile, desktop, and server processors are heterogeneous, consisting not only of CPUs but also GPUs and other accelerators. Such heterogeneous processors are starting to expose a shared memory interface across these devices. Given that each of these individual devices typically support a distinct instruction set architecture and a distinct memory consistency model, it is not clear what the memory consistency model of the heterogeneous machine should be. In this paper, we answer this question by formalizing “compound” consistency models: we present a compositional operational model describing the resulting model when devices with distinct consistency models are fused together. We instantiate our model with the compound x86TSO/PTX model – a CPU enforcing x86TSO and a GPU enforcing the PTX model. A key result is that the x86TSO/PTX compound model retains compiler mappings from the language-based (scoped) C memory model. This means that threads mapped to the x86TSO device can continue to use the already proven C-to-x86TSO compiler mapping, and the same for PTX.
Citation
Goens , A , Chakraborty , S , Sarkar , S , Agarwal , S , Oswald , N & Nagarajan , V 2023 , ' Compound memory models ' , Proceedings of the ACM on Programming Languages , vol. 7 , no. PLDI , 153 . https://doi.org/10.1145/3591267
Publication
Proceedings of the ACM on Programming Languages
Status
Peer reviewed
DOI
https://doi.org/10.1145/3591267
ISSN
2475-1421
Type
Journal article
Rights
Copyright © 2023 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution 4.0 Internationa lLicense.
Description
Funding: This work was funded by the Engineering and Physical Sciences Research Council, through grant references EP/V038699/1 and EP/V028154/1. Submitted to PLDI 2023, which will publish accepted papers in the Proceedings of the ACM in Programming Languages (PACMPL).
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/27764

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