852 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Investigations into Proof Structures

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    We introduce and elaborate a novel formalism for the manipulation and analysis of proofs as objects in a global manner. In this first approach the formalism is restricted to first-order problems characterized by condensed detachment. It is applied in an exemplary manner to a coherent and comprehensive formal reconstruction and analysis of historical proofs of a widely-studied problem due to {\L}ukasiewicz. The underlying approach opens the door towards new systematic ways of generating lemmas in the course of proof search to the effects of reducing the search effort and finding shorter proofs. Among the numerous reported experiments along this line, a proof of {\L}ukasiewicz's problem was automatically discovered that is much shorter than any proof found before by man or machine.Comment: This article is a continuation of arXiv:2104.1364

    (b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!)

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    (b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!

    The Quantum Monadology

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    The modern theory of functional programming languages uses monads for encoding computational side-effects and side-contexts, beyond bare-bone program logic. Even though quantum computing is intrinsically side-effectful (as in quantum measurement) and context-dependent (as on mixed ancillary states), little of this monadic paradigm has previously been brought to bear on quantum programming languages. Here we systematically analyze the (co)monads on categories of parameterized module spectra which are induced by Grothendieck's "motivic yoga of operations" -- for the present purpose specialized to HC-modules and further to set-indexed complex vector spaces. Interpreting an indexed vector space as a collection of alternative possible quantum state spaces parameterized by quantum measurement results, as familiar from Proto-Quipper-semantics, we find that these (co)monads provide a comprehensive natural language for functional quantum programming with classical control and with "dynamic lifting" of quantum measurement results back into classical contexts. We close by indicating a domain-specific quantum programming language (QS) expressing these monadic quantum effects in transparent do-notation, embeddable into the recently constructed Linear Homotopy Type Theory (LHoTT) which interprets into parameterized module spectra. Once embedded into LHoTT, this should make for formally verifiable universal quantum programming with linear quantum types, classical control, dynamic lifting, and notably also with topological effects.Comment: 120 pages, various figure

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Canonicity of Proofs in Constructive Modal Logic

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    In this paper we investigate the Curry-Howard correspondence for constructive modal logic in light of the gap between the proof equivalences enforced by the lambda calculi from the literature and by the recently defined winning strategies for this logic. We define a new lambda-calculus for a minimal constructive modal logic by enriching the calculus from the literature with additional reduction rules and we prove normalization and confluence for our calculus. We then provide a typing system in the style of focused proof systems allowing us to provide a unique proof for each term in normal form, and we use this result to show a one-to-one correspondence between terms in normal form and winning innocent strategies.Comment: Extended version of the TABLEAUX 2023 pape

    IMPLICATIONS OF AFRO-COMMUNITARIAN ETHICS FOR SOCIALLY RESPONSIBLE BEHAVIOUR IN THE INFORMAL SECTOR::A CASE OF AKAN SOLE TRADERS IN CAPE COAST, GHANA.

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    In the same way that small businesses were left out of the drive towards corporate social responsibility (CSR), they seem to have been excluded from the business human rights (BHR) agenda as well. Both CSR and its more recent outgrowth, Business Human Rights (BHR), emphasize the need for business organizations to engage in responsible and socially beneficial activities. What is clear from the literature is that, like CSR, BHR has primarily focused on businesses in the formal sector, particularly Transnational Corporations (TNCs), with only minimal attention paid to Micro, Small, and Medium Enterprises (MSMEs), particularly sole traders, operating within the informal economy. This lack of attention has resulted in a scarcity of empirical investigations into whether informal micro-enterprises, such as sole traders, undertake socially responsible behaviour beyond the well-documented economic contributions they make. As this study will show, informal sole traders do undertake some CSR activities, particularly philanthropic activities, which also fulfil some business human rights obligations. In line with this, the following research questions were crafted: What socially responsible actions, particularly philanthropic responsibilities, do informal sole traders undertake? How do these actions fulfil some business human rights obligations as laid out in the United Nations Framework for Business Human Rights? And what motivates such socially responsible behaviours? Fanti sole traders living and operating in the Abura community of Cape Coast, the capital city of the Central Region, Ghana, were selected as the research context. The study followed an inductive pathway of inquiry and employed semi-structured interviews and non-participant observation. Thirty sole traders involved in various petty trades, such as second-hand clothes sellers, food vendors, and iced-water sellers, were interviewed. This was supported with data collected through non-participant observations, all in line with the qualitative nature of the study. Collected data was manually analyzed using thematic analysis. In terms of a theoretical framework, a modified version of Integrative Social Contracts Theory (ISCT) was used. This theory provides a blueprint for how informal sole traders can make socially responsible business choices and decisions in the conduct of their business, which also fulfills some business human rights obligations. This is especially beneficial in the absence of a prescriptive and conclusive set of directions on how such businesses are to act responsibly by agreeing on a set of normative rules in the form of micro-social contracts towards stakeholders—something the authors of ISCT attribute to the bounded rationality of economic morality. In the present study, it was proposed that the norms inherent in Afro-communitarianism, reputed to be the authentic African ethic, constitute the content of micro-social contracts. According to ISCT, if local community members (such as informal sole traders) freely subscribe to these norms and retain the right to exit the community, they attain legitimacy. Furthermore, if legitimate norms harmonize with hypernorms, a key example of which is the provisions in the UDHR, then they become authentic norms. The study provides an empirical contribution to the area of small business social responsibility by showing that despite their apparent illegality, informal business communities made up of sole traders do exhibit some socially responsible behaviour, some of which neatly overlaps with certain BHR obligations. The study contributes to theory by introducing the concept of "superfluous norms" — explained as authentic norms that significantly surpass hypernorms instead of merely meeting the minimum threshold of hypernorms

    Deployment of Deep Neural Networks on Dedicated Hardware Accelerators

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    Deep Neural Networks (DNNs) have established themselves as powerful tools for a wide range of complex tasks, for example computer vision or natural language processing. DNNs are notoriously demanding on compute resources and as a result, dedicated hardware accelerators for all use cases are developed. Different accelerators provide solutions from hyper scaling cloud environments for the training of DNNs to inference devices in embedded systems. They implement intrinsics for complex operations directly in hardware. A common example are intrinsics for matrix multiplication. However, there exists a gap between the ecosystems of applications for deep learning practitioners and hardware accelerators. HowDNNs can efficiently utilize the specialized hardware intrinsics is still mainly defined by human hardware and software experts. Methods to automatically utilize hardware intrinsics in DNN operators are a subject of active research. Existing literature often works with transformationdriven approaches, which aim to establish a sequence of program rewrites and data-layout transformations such that the hardware intrinsic can be used to compute the operator. However, the complexity this of task has not yet been explored, especially for less frequently used operators like Capsule Routing. And not only the implementation of DNN operators with intrinsics is challenging, also their optimization on the target device is difficult. Hardware-in-the-loop tools are often used for this problem. They use latency measurements of implementations candidates to find the fastest one. However, specialized accelerators can have memory and programming limitations, so that not every arithmetically correct implementation is a valid program for the accelerator. These invalid implementations can lead to unnecessary long the optimization time. This work investigates the complexity of transformation-driven processes to automatically embed hardware intrinsics into DNN operators. It is explored with a custom, graph-based intermediate representation (IR). While operators like Fully Connected Layers can be handled with reasonable effort, increasing operator complexity or advanced data-layout transformation can lead to scaling issues. Building on these insights, this work proposes a novel method to embed hardware intrinsics into DNN operators. It is based on a dataflow analysis. The dataflow embedding method allows the exploration of how intrinsics and operators match without explicit transformations. From the results it can derive the data layout and program structure necessary to compute the operator with the intrinsic. A prototype implementation for a dedicated hardware accelerator demonstrates state-of-the art performance for a wide range of convolutions, while being agnostic to the data layout. For some operators in the benchmark, the presented method can also generate alternative implementation strategies to improve hardware utilization, resulting in a geo-mean speed-up of ×2.813 while reducing the memory footprint. Lastly, by curating the initial set of possible implementations for the hardware-in-the-loop optimization, the median timeto- solution is reduced by a factor of ×2.40. At the same time, the possibility to have prolonged searches due a bad initial set of implementations is reduced, improving the optimization’s robustness by ×2.35
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