With the increasing miniaturization of transistors, wire delays are becoming a dominant factor in microprocessor performance. To address this issue, a number of emerging architectures contain replicated processing units with software-exposed communication between one unit and another (e.g., Raw, SmartMemories, TRIPS). However, for their use to be widespread, it will be necesary to develop a common machine language to allow programmers to express an algorithm in a way that can be efficiently mapped across these architectures. We propose a new common machine language for grid-based software-exposed architectures: StreamIt. StreamIt is a high-level programming language with explicit support for streaming computation. Unlike sequential programs with obscured dependence information and complex communication patterns, a stream program is naturally written as a set of concurrent filters with regular steady-state communication. The language imposes a hierarchical structure on the stream graph that enables novel representations and optimizations within the StreamIt compiler. We have implemented a fully functional compiler that parallelizes StreamIt applications for Raw, including several load-balancing transformations. Though StreamIt exposes the parallelism and communication patterns of stream programs, analysis is needed to adapt a stream program to a software-exposed processor. We describe a partitioning algorithm that employs fission and fusion transformations to adjust the granularity of a stream graph, a layout algorithm that maps a stream graph to a given network topology, and a scheduling strategy that generates a fine-grained static communication pattern for each computational element. Using the cycle-accurate Raw simulator, we demonstrate that the StreamIt compiler can automatically map a high-level stream abstraction to Raw. We consider this work to be a first step towards a portable programming model for communication-exposed architectures. / Singapore-MIT Alliance (SMA)

Recent progress in the field of quantum computers provide radically improved muscles to search and sort in lists, solve systems of equations and prime factorize – virtues that inflict an immediate threat to the most common systems for public key cryptography used in a vast proportion of today’s computer networks. NTRUEncrypt is a lattice-based cryptography system which inhibits quantum computers for breaking the algorithm in polynomial time. The cryptographic algorithm is one of the seventeen that passed the first round in the NIST Post-Quantum standardisation competition which serves an indication that this system is robust against the efforts from a cryptanalysist to compromise its security properties. With the development of a server and client application that is built using Python3 integrated with WolfSSL, the results obtained from the experiment show that the suggested model acquires the capabilities to overcome the quantum computers capacities, providing fast quantum-safe asymmetric encryption algorithm for TLS communication in smart homes. The handshake process with NTRUEncrypt and WolfSSL is proven to be significantly faster comparing to other algorithms tested.

Fuzzy description logics can be used to model vague knowledge in application domains. This paper analyses the consistency and satisfiability problems in the description logic SHI with semantics based on a complete residuated De Morgan lattice. The problems are undecidable in the general case, but can be decided by a tableau algorithm when restricted to finite lattices. For some sublogics of SHI, we provide upper complexity bounds that match the complexity of crisp reasoning.