Visibility reasoning for concurrent snapshot algorithms

Visibility relations have been proposed by Henzinger et al. as an abstraction for proving linearizability of concurrent algorithms that obtains modular and reusable proofs. This is in contrast to the customary approach based on exhibiting the algorithm's linearization points. In this paper we apply visibility relations to develop modular proofs for three elegant concurrent snapshot algorithms of Jayanti. The proofs are divided by signatures into components of increasing level of abstraction; the components at higher abstraction levels are shared, i.e., they apply to all three algorithms simultaneously. Importantly, the interface properties mathematically capture Jayanti's original intuitions that have previously been given only informally.

A Pragmatic Approach for Detecting nCOVID-19 using Pervasive Computing Based on Dual Diagnostic Measures

Our regular way of life has been disrupted by the COVID-19, and we have been obliged to accept the procedures that are in place under the new normal regime. It is envisaged that the standard diagnostic technique will evolve throughout the course of the procedure. As a help to this type of diagnostic technique, our research group is developing a tool. In this article, the group discusses the importance of employing two diagnostic metrics that have proven to be pivotal in many diagnoses for doctors, and how they might be used to their advantage. Together, natural language processing-based symptoms measures and a machine learning-based strategy that takes into account medical vitals can help to minimise the error percentage of detection by as much as 50%. The technique suggested in this study is the first of its type, and the authors have obtained findings that are satisfactory in terms of accuracy. A further justification for suggesting such a strategy is the manner in which a fusion algorithm might arrive at the correct results from two concurrent algorithms performing the same task. One of the group's other objectives was to give the doctor a valuable opinion in the form of such an architectural design. The suggested design may be employed at any point of care facility without the need for any additional infrastructure or escalation of the current amenities to accommodate the proposed architecture.

Concurrent disjoint set union

We develop and analyze concurrent algorithms for the disjoint set union (“union-find” ) problem in the shared memory, asynchronous multiprocessor model of computation, with CAS (compare and swap) or DCAS (double compare and swap) as the synchronization primitive. We give a deterministic bounded wait-free algorithm that uses DCAS and has a total work bound of $$O\biggl ( m \cdot \left( \log {\left( \frac{np}{m} + 1 \right) } + \alpha {\left( n, \frac{m}{np} \right) } \right) \biggr )$$ O ( m · log np m + 1 + α n , m np ) for a problem with n elements and m operations solved by p processes, where $$\alpha $$ α is a functional inverse of Ackermann’s function. We give two randomized algorithms that use only CAS and have the same work bound in expectation. The analysis of the second randomized algorithm is valid even if the scheduler is adversarial. Our DCAS and randomized algorithms take $$O(\log n)$$ O ( log n ) steps per operation, worst-case for the DCAS algorithm, high-probability for the randomized algorithms. Our work and step bounds grow only logarithmically with p, making our algorithms truly scalable. We prove that for a class of symmetric algorithms that includes ours, no better step or work bound is possible. Our work is theoretical, but Alistarh et al (In search of the fastest concurrent union-find algorithm, 2019), Dhulipala et al (A framework for static and incremental parallel graph connectivity algorithms, 2020) and Hong et al (Exploring the design space of static and incremental graph connectivity algorithms on gpus, 2020) have implemented some of our algorithms on CPUs and GPUs and experimented with them. On many realistic data sets, our algorithms run as fast or faster than all others.

Rely-guarantee bound analysis of parameterized concurrent shared-memory programs

We present a thread-modular proof method for complexity and resource bound analysis of concurrent, shared-memory programs. To this end, we lift Jones’ rely-guarantee reasoning to assumptions and commitments capable of expressing bounds. The compositionality (thread-modularity) of this framework allows us to reason about parameterized programs, i.e., programs that execute arbitrarily many concurrent threads. We automate reasoning in our logic by reducing bound analysis of concurrent programs to the sequential case. As an application, we automatically infer time complexity for a family of fine-grained concurrent algorithms, lock-free data structures, to our knowledge for the first time.

A Behavioural Theory of Recursive Algorithms

“What is an algorithm?” is a fundamental question of computer science. Gurevich’s behavioural theory of sequential algorithms (aka the sequential ASM thesis) gives a partial answer by defining (non-deterministic) sequential algorithms axiomatically, without referring to a particular machine model or programming language, and showing that they are captured by (nondeterministic) sequential Abstract State Machines (nd-seq ASMs). However, recursive algorithms such as mergesort are not covered by this theory, as has been pointed out by Moschovakis, who had independently developed a different framework to mathematically characterize the concept of (in particular recursive) algorithm. In this article we propose an axiomatic definition of the notion of sequential recursive algorithm which extends Gurevich’s axioms for sequential algorithms by a Recursion Postulate and allows us to prove that sequential recursive algorithms are captured by recursive Abstract State Machines, an extension of nd-seq ASMs by a CALL rule. Applying this recursive ASM thesis yields a characterization of sequential recursive algorithms as finitely composed concurrent algorithms all of whose concurrent runs are partial-order runs.

Atomic, Wireless Methodologies for Symmetric Encryption

Unified concurrent algorithms have prompted many key advances, including compose back reserves and Smalltalk. Given the flow status of steady time models, analysts amazingly want the improvement of open private key sets. We verify that Moore's Law [6] can be made cacheable, relational.

Active Noise Control proposal design enhanced because of using sensors/actuators based on nanostructures

Big machines and motors, that under operating work produces high decibels of noise in wide range of work, these values are near 90 dB that is not healthy for humans. Normally, it is used passive mechanisms to attenuate noise such as big headphones. However that solution is not enough when noise has changes in frequency domain. Therefore, it is proposed in this work a solution by noise cancellation with Active Mechanisms; nevertheless, we designed a hybrid algorithm improved through predictive/adaptive concurrent algorithms strategies, with Active Noise Cancellation (ANC). By other side, based on nanostructures, it has been analyzed the effect in robustness and wide range of work by frequency domain in order to enhance noise cancellation.