On proving the equivalence of concurrency primitives

Various concurrency primitives have been added to sequential programming languages, in order to turn them concurrent. Prominent examples are concurrent buffers for Haskell, channels in Concurrent ML, joins in JoCaml, and handled futures in Alice ML. Even though one might conjecture that all these primitives provide the same expressiveness, proving this equivalence is an open challenge in the area of program semantics. In this paper, we establish a first instance of this conjecture. We show that concurrent buffers can be encoded in the lambda calculus with futures underlying Alice ML. Our correctness proof results from a systematic method, based on observational semantics with respect to may and must convergence

Aerobic fitness impacts sympathoadrenal axis responses to concurrent challenges

The combination of mental and physical challenges can elicit exacerbated cardiorespiratory (CR) and catecholamine responses above that of a single challenge alone. Purpose This study examined the effects of a combination of acute mental challenges and physical stress on cardiorespiratory and catecholamine responses. Method Eight below-average fitness (LF VO2max = 36.58 +/- 3.36 ml(-1) kg(-1) min(-1)) and eight above-average fitness (HF VO2max = 51.18 +/- 2.09 ml(-1) kg(-1) min(-1)) participants completed an exercise-alone condition (EAC) session consisting of moderate-intensity cycling at 60% VO2max for 37 min, and a dual-challenge condition (DCC) that included concurrent participation in mental challenges while cycling. Result The DCC resulted in increases in perceived workload, CR, epinephrine, and norepinephrine responses overall. HF participants had greater absolute CR and catecholamine responses compared to LF participants and quicker HR recovery after the dual challenge. Conclusion These findings demonstrate that cardiorespiratory fitness does impact the effect of concurrent stressors on CR and catecholamine responses

On correctness of buffer implementations in a concurrent lambda calculus with futures

Motivated by the question of correctness of a specific implementation of concurrent buffers in the lambda calculus with futures underlying Alice ML, we prove that concurrent buffers and handled futures can correctly encode each other. Correctness means that our encodings preserve and reflect the observations of may- and must-convergence. This also shows correctness wrt. program semantics, since the encodings are adequate translations wrt. contextual semantics. While these translations encode blocking into queuing and waiting, we also provide an adequate encoding of buffers in a calculus without handles, which is more low-level and uses busy-waiting instead of blocking. Furthermore we demonstrate that our correctness concept applies to the whole compilation process from high-level to low-level concurrent languages, by translating the calculus with buffers, handled futures and data constructors into a small core language without those constructs

Program equivalence for a concurrent lambda calculus with futures

Reasoning about the correctness of program transformations requires a notion of program equivalence. We present an observational semantics for the concurrent lambda calculus with futures Lambda(fut), which formalizes the operational semantics of the programming language Alice ML. We show that natural program optimizations, as well as partial evaluation with respect to deterministic rules, are correct for Lambda(fut). This relies on a number of fundamental properties that we establish for our observational semantics

Concurrent Classifier Error Detection (CCED) in Large Scale Machine Learning Systems

The complexity of Machine Learning (ML) systems increases each year, with current implementations of large language models or text-to-image generators having billions of parameters and requiring billions of arithmetic operations. As these systems are widely utilized, ensuring their reliable operation is becoming a design requirement. Traditional error detection mechanisms introduce circuit or time redundancy that significantly impacts system performance. An alternative is the use of Concurrent Error Detection (CED) schemes that operate in parallel with the system and exploit their properties to detect errors. CED is attractive for large ML systems because it can potentially reduce the cost of error detection. In this paper, we introduce Concurrent Classifier Error Detection (CCED), a scheme to implement CED in ML systems using a concurrent ML classifier to detect errors. CCED identifies a set of check signals in the main ML system and feeds them to the concurrent ML classifier that is trained to detect errors. The proposed CCED scheme has been implemented and evaluated on two widely used large-scale ML models: Contrastive Language Image Pretraining (CLIP) used for image classification and Bidirectional Encoder Representations from Transformers (BERT) used for natural language applications. The results show that more than 95 percent of the errors are detected when using a simple Random Forest classifier that is order of magnitude simpler than CLIP or BERT. These results illustrate the potential of CCED to implement error detection in large-scale ML models

Outcomes and safety of concomitant nevirapine and rifampicin treatment under programme conditions in Malawi.

SETTING: Thyolo District Hospital, rural Malawi. OBJECTIVES: To report on 1) clinical, immunological and virological outcomes and 2) safety among human immunodeficiency virus (HIV) infected patients with tuberculosis (TB) who received concurrent nevirapine (NVP) and rifampicin (RMP) based treatment. DESIGN: Retrospective cohort study. METHODS: Analysis of programme data, June-December 2007. RESULTS: Of a total of 156 HIV-infected TB patients who started NVP-based antiretroviral treatment, 136 (87%) completed TB treatment successfully, 16 (10%) died and 5 (4%) were transferred out. Mean body weight and CD4 gain (adults) were respectively 4.4 kg (95%CI 3.3-5.4) and 140 cells/mm(3) (95%CI 117-162). Seventy-four per cent of patients who completed TB treatment and had a viral load performed (n = 74) had undetectable levels (<50 copies/ml), while 17 (22%) had a viral load of 50-1000 copies/ml. Hepatotoxicity was present in 2 (1.3%) patients at baseline. Two patients developed Grade 2 and one developed Grade 3 alanine transaminase enzyme elevations during TB treatment (incidence rate per 10 years of follow-up 4.2, 95%CI 1.4-13.1). There were no reported deaths linked to hepatotoxicity. CONCLUSIONS: In a rural district in Malawi, concomitant NVP and RMP treatment is associated with good TB treatment outcomes and appears safe. Further follow-up of patients would be useful to ascertain the longer-term effects of this concurrent treatment

Programming Idioms for Transactional Events

Transactional events (TE) are an extension of Concurrent ML (CML), a programming model for synchronous message-passing. Prior work has focused on TE's formal semantics and its implementation. This paper considers programming idioms, particularly those that vary unexpectedly from the corresponding CML idioms. First, we solve a subtle problem with client-server protocols in TE. Second, we argue that CML's wrap and guard primitives do not translate well to TE, and we suggest useful workarounds. Finally, we discuss how to rewrite CML protocols that use abort actions

Polymorphic Subtyping for Effect Analysis: The Semantics

We study an annotated type and effect system that integrates let-polymorphism, effects, and subtyping into an annotated type and effect system for a fragment of Concurrent ML. First a small step operational semantics is defined for concurrent ML and next the annotated type and effect system is proved semantically sound. This provides insights into the rule for generalisation in the annotated type and effect system