5 Search Results for "Singh, Abhishek"

Document
DOI: 10.4230/LIPIcs.ECOOP.2024.32
Tenspiler: A Verified-Lifting-Based Compiler for Tensor Operations

Authors: Jie Qiu, Colin Cai, Sahil Bhatia, Niranjan Hasabnis, Sanjit A. Seshia, and Alvin Cheung

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Tensor processing infrastructures such as deep learning frameworks and specialized hardware accelerators have revolutionized how computationally intensive code from domains such as deep learning and image processing is executed and optimized. These infrastructures provide powerful and expressive abstractions while ensuring high performance. However, to utilize them, code must be written specifically using the APIs / ISAs of such software frameworks or hardware accelerators. Importantly, given the fast pace of innovation in these domains, code written today quickly becomes legacy as new frameworks and accelerators are developed, and migrating such legacy code manually is a considerable effort. To enable developers in leveraging such DSLs while preserving their current programming paradigm, we present Tenspiler, a verified-lifting-based compiler that uses program synthesis to translate sequential programs written in general-purpose programming languages (e.g., C++ or Python code that does not leverage any specialized framework or accelerator) into tensor operations. Central to Tenspiler is our carefully crafted yet simple intermediate language, named TensIR, that expresses tensor operations. TensIR enables efficient lifting, verification, and code generation. Unlike classical pattern-matching-based compilers, Tenspiler uses program synthesis to translate input code into TensIR, which is then compiled to the target API / ISA. Currently, Tenspiler already supports six DSLs, spanning a broad spectrum of software and hardware environments. Furthermore, we show that new backends can be easily supported by Tenspiler by adding simple pattern-matching rules for TensIR. Using 10 real-world code benchmark suites, our experimental evaluation shows that by translating code to be executed on 6 different software frameworks and hardware devices, Tenspiler offers on average 105× kernel and 9.65× end-to-end execution time improvement over the fully-optimized sequential implementation of the same benchmarks.
Cite as

Jie Qiu, Colin Cai, Sahil Bhatia, Niranjan Hasabnis, Sanjit A. Seshia, and Alvin Cheung. Tenspiler: A Verified-Lifting-Based Compiler for Tensor Operations. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 32:1-32:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{qiu_et_al:LIPIcs.ECOOP.2024.32,
  author =	{Qiu, Jie and Cai, Colin and Bhatia, Sahil and Hasabnis, Niranjan and Seshia, Sanjit A. and Cheung, Alvin},
  title =	{{Tenspiler: A Verified-Lifting-Based Compiler for Tensor Operations}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{32:1--32:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.32},
  URN =		{urn:nbn:de:0030-drops-208817},
  doi =		{10.4230/LIPIcs.ECOOP.2024.32},
  annote =	{Keywords: Program Synthesis, Code Transpilation, Tensor DSLs, Verification}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.43
Inductive Predicate Synthesis Modulo Programs

Authors: Scott Wesley, Maria Christakis, Jorge A. Navas, Richard Trefler, Valentin Wüstholz, and Arie Gurfinkel

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
A growing trend in program analysis is to encode verification conditions within the language of the input program. This simplifies the design of analysis tools by utilizing off-the-shelf verifiers, but makes communication with the underlying solver more challenging. Essentially, the analysis tools operates at the level of input programs, whereas the solver operates at the level of problem encodings. To bridge this gap, the verifier must pass along proof-rules from the analysis tool to the solver. For example, an analysis tool for concurrent programs built on an inductive program verifier might need to declare Owicki-Gries style proof-rules for the underlying solver. Each such proof-rule further specifies how a program should be verified, meaning that the problem of passing proof-rules is a form of invariant synthesis. Similarly, many program analysis tasks reduce to the synthesis of pure, loop-free Boolean functions (i.e., predicates), relative to a program. From this observation, we propose Inductive Predicate Synthesis Modulo Programs (IPS-MP) which extends high-level languages with minimal synthesis features to guide analysis. In IPS-MP, unknown predicates appear under assume and assert statements, acting as specifications modulo the program semantics. Existing synthesis solvers are inefficient at IPS-MP as they target more general problems. In this paper, we show that IPS-MP admits an efficient solution in the Boolean case, despite being generally undecidable. Moreover, we show that IPS-MP reduces to the satisfiability of constrained Horn clauses, which is less general than existing synthesis problems, yet expressive enough to encode verification tasks. We provide reductions from challenging verification tasks - such as parameterized model checking - to IPS-MP. We realize these reductions with an efficient IPS-MP-solver based on SeaHorn, and describe a real-world application to smart-contract verification.
Cite as

Scott Wesley, Maria Christakis, Jorge A. Navas, Richard Trefler, Valentin Wüstholz, and Arie Gurfinkel. Inductive Predicate Synthesis Modulo Programs. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 43:1-43:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{wesley_et_al:LIPIcs.ECOOP.2024.43,
  author =	{Wesley, Scott and Christakis, Maria and Navas, Jorge A. and Trefler, Richard and W\"{u}stholz, Valentin and Gurfinkel, Arie},
  title =	{{Inductive Predicate Synthesis Modulo Programs}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{43:1--43:30},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.43},
  URN =		{urn:nbn:de:0030-drops-208926},
  doi =		{10.4230/LIPIcs.ECOOP.2024.43},
  annote =	{Keywords: Software Verification, Invariant Synthesis, Model-Checking}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2024.13
DeepTrust^RT: Confidential Deep Neural Inference Meets Real-Time!

Authors: Mohammad Fakhruddin Babar and Monowar Hasan

Published in: LIPIcs, Volume 298, 36th Euromicro Conference on Real-Time Systems (ECRTS 2024)

Abstract
Deep Neural Networks (DNNs) are becoming common in "learning-enabled" time-critical applications such as autonomous driving and robotics. One approach to protect DNN inference from adversarial actions and preserve model privacy/confidentiality is to execute them within trusted enclaves available in modern processors. However, running DNN inference inside limited-capacity enclaves while ensuring timing guarantees is challenging due to (a) large size of DNN workloads and (b) extra switching between "normal" and "trusted" execution modes. This paper introduces new time-aware scheduling schemes - DeepTrust^RT - to securely execute deep neural inferences for learning-enabled real-time systems. We first propose a variant of EDF (called DeepTrust^RT-LW) that slices each DNN layer and runs them sequentially in the enclave. However, due to extra context switch overheads of individual layer slices, we further introduce a novel layer fusion technique (named DeepTrust^RT-FUSION). Our proposed scheme provides hard real-time guarantees by fusing multiple layers of DNN workload from multiple tasks; thus allowing them to fit and run concurrently within the enclaves while maintaining real-time guarantees. We implemented and tested DeepTrust^RT ideas on the Raspberry Pi platform running OP-TEE+DarkNet-TZ DNN APIs and three DNN workloads (AlexNet-squeezed, Tiny Darknet, YOLOv3-tiny). Compared to the layer-wise partitioning approach (DeepTrust^RT-LW), DeepTrust^RT-FUSION can schedule up to 3x more tasksets and reduce context switches by up to 11.12x. We further demonstrate the efficacy of DeepTrust^RT using a flight controller (ArduPilot) case study and find that DeepTrust^RT-FUSION retains real-time guarantees where DeepTrust^RT-LW becomes unschedulable.
Cite as

Mohammad Fakhruddin Babar and Monowar Hasan. DeepTrust^RT: Confidential Deep Neural Inference Meets Real-Time!. In 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 298, pp. 13:1-13:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{babar_et_al:LIPIcs.ECRTS.2024.13,
  author =	{Babar, Mohammad Fakhruddin and Hasan, Monowar},
  title =	{{DeepTrust^RT: Confidential Deep Neural Inference Meets Real-Time!}},
  booktitle =	{36th Euromicro Conference on Real-Time Systems (ECRTS 2024)},
  pages =	{13:1--13:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-324-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{298},
  editor =	{Pellizzoni, Rodolfo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2024.13},
  URN =		{urn:nbn:de:0030-drops-203161},
  doi =		{10.4230/LIPIcs.ECRTS.2024.13},
  annote =	{Keywords: DNN, TrustZone, Real-Time Systems}
}
Document
DOI: 10.4230/LIPIcs.ITP.2021.28
Verified Double Sided Auctions for Financial Markets

Authors: Raja Natarajan, Suneel Sarswat, and Abhishek Kr Singh

Published in: LIPIcs, Volume 193, 12th International Conference on Interactive Theorem Proving (ITP 2021)

Abstract
Double sided auctions are widely used in financial markets to match demand and supply. Prior works on double sided auctions have focused primarily on single quantity trade requests. We extend various notions of double sided auctions to incorporate multiple quantity trade requests and provide fully formalized matching algorithms for double sided auctions with their correctness proofs. We establish new uniqueness theorems that enable automatic detection of violations in an exchange program by comparing its output with that of a verified program. All proofs are formalized in the Coq proof assistant without adding any axiom to the system. We extract verified OCaml and Haskell programs that can be used by the exchanges and the regulators of the financial markets. We demonstrate the practical applicability of our work by running the verified program on real market data from an exchange to automatically check for violations in the exchange algorithm.
Cite as

Raja Natarajan, Suneel Sarswat, and Abhishek Kr Singh. Verified Double Sided Auctions for Financial Markets. In 12th International Conference on Interactive Theorem Proving (ITP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 193, pp. 28:1-28:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{natarajan_et_al:LIPIcs.ITP.2021.28,
  author =	{Natarajan, Raja and Sarswat, Suneel and Singh, Abhishek Kr},
  title =	{{Verified Double Sided Auctions for Financial Markets}},
  booktitle =	{12th International Conference on Interactive Theorem Proving (ITP 2021)},
  pages =	{28:1--28:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-188-7},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{193},
  editor =	{Cohen, Liron and Kaliszyk, Cezary},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITP.2021.28},
  URN =		{urn:nbn:de:0030-drops-139230},
  doi =		{10.4230/LIPIcs.ITP.2021.28},
  annote =	{Keywords: Double Sided Auction, Formal Verification, Financial Markets, Proof Assistant}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2017.8
Applying Real-Time Scheduling Theory to the Synchronous Data Flow Model of Computation

Authors: Abhishek Singh, Pontus Ekberg, and Sanjoy Baruah

Published in: LIPIcs, Volume 76, 29th Euromicro Conference on Real-Time Systems (ECRTS 2017)

Abstract
Schedulability analysis techniques that are well understood within the real-time scheduling community are applied to the analysis of recurrent real-time workloads that are modeled using the synchronous data-flow graph (SDFG) model. An enhancement to the standard SDFG model is proposed, that permits the specification of a real-time latency constraint between a specified input and a specified output of an SDFG. A technique is derived for transforming such an enhanced SDFG to a collection of traditional 3-parameter sporadic tasks, thereby allowing for the analysis of systems of SDFG tasks using the methods and algorithms that have previously been developed within the real-time scheduling community for the analysis of systems of such sporadic tasks. The applicability of this approach is illustrated by applying prior results from real-time scheduling theory to construct an exact preemptive uniprocessor schedulability test for collections of recurrent processes that are each represented using the enhanced SDFG model.
Cite as

Abhishek Singh, Pontus Ekberg, and Sanjoy Baruah. Applying Real-Time Scheduling Theory to the Synchronous Data Flow Model of Computation. In 29th Euromicro Conference on Real-Time Systems (ECRTS 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 76, pp. 8:1-8:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{singh_et_al:LIPIcs.ECRTS.2017.8,
  author =	{Singh, Abhishek and Ekberg, Pontus and Baruah, Sanjoy},
  title =	{{Applying Real-Time Scheduling Theory to the Synchronous Data Flow Model of Computation}},
  booktitle =	{29th Euromicro Conference on Real-Time Systems (ECRTS 2017)},
  pages =	{8:1--8:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-037-8},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{76},
  editor =	{Bertogna, Marko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2017.8},
  URN =		{urn:nbn:de:0030-drops-71517},
  doi =		{10.4230/LIPIcs.ECRTS.2017.8},
  annote =	{Keywords: Real-Time Systems, Synchronous Dataflow (SDF), Hard Real-Time Streaming Dataflow Applications, Algorithms}
}
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