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Computer Science > Programming Languages

arXiv:2406.10405 (cs)
[Submitted on 14 Jun 2024]

Title:Correctness is Demanding, Performance is Frustrating

Authors:Artjoms Sinkarovs, Thomas Koopman, Sven-Bodo Scholz
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Abstract:In this paper we demonstrate a technique for developing high performance applications with strong correctness guarantees. We use a theorem prover to derive a high-level specification of the application that includes correctness invariants of our choice. After that, within the same theorem prover, we implement an extraction of the specified application into a high-performance language of our choice. Concretely, we are using Agda to specify a framework for automatic differentiation (reverse mode) that is focused on index-safe tensors. This framework comes with an optimiser for tensor expressions and the ability to translate these expressions into SaC and C. We specify a canonical convolutional neural network within the proposed framework, compute the derivatives needed for the training phase and then demonstrate that the generated code matches the performance of hand-written code when running on a multi-core machine.
Subjects: Programming Languages (cs.PL)
Cite as: arXiv:2406.10405 [cs.PL]
  (or arXiv:2406.10405v1 [cs.PL] for this version)
  https://doi.org/10.48550/arXiv.2406.10405

Submission history

From: Artjoms Sinkarovs PhD [view email]
[v1] Fri, 14 Jun 2024 20:15:25 UTC (126 KB)
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