Journal of Information Technology & Software Engineering
Open Access

Transformations for High-Performance Computing

Jonice Oliveira^{* *}Correspondence: Jonice Oliveira, Department of Computer Science, Universidad Federal do Rio de Janeiro, Rio de Janeiro, Brazil, Email:

Author info »

Introduction

Programmers wishing to enhance the performance of their code can use this survey to improve their understanding of the optimizations that compilers can perform, or as a reference for techniques to be applied manually. Students can obtain an overview of optimizing compiler technology. Compiler writers can use this survey as a reference for most of the important optimizations developed to date, and as bibliographic reference for the details of each optimization. Readers are expected to be familiar with modern computer architecture and basic program compilation techniques. Cloud computing empowered Internet of Things (IoT) technology has conceptualized the ideology of Industry 4.0. Inspired by this, the food industry 4.0 presents a unique concept for determining food quality in real-time. Conspicuously, the current research provides an IoT-based smart framework for evaluating the food-quality parameters in restaurants and food outlets. IoT technology is primarily utilized to gather data that can explicitly affect food quality within a food serving environment. Such data is analyzed using the Bayesian Modeling Technique on the Fog-Cloud platform to derive a unanimous metric in terms of Probability of Food Grade (PoFG). Also, Food Grade Assessment Scale (FGAS) is quantified to assess real-time food-oriented parameters in the ambient environment of food-outlets and restaurants.

Transformation Issues

Decide upon a part of the program to optimize and a particular transformation to apply to it. Verify that the transformation either does not change the meaning of the program or changes it in a restricted way that is acceptable to the user. Transform the program. In this survey we concentrate on the last step: transformation of the program. On determinism can be introduced by language constructs or by calls to system or library routines that return information about the state external to the program (such as Unix time( ) or read()). In some cases it is straightforward to cause executions to be identical, for instance by entering the same inputs, In other cases there may be support for determinism in the programming environment for instance, a compilation option that forces select statements to evaluate their guards in a deterministic order. As a last resort, the programmer may have to replace nondeterministic system calls temporarily with deterministic operations in order to compare two versions.

Conclusion

Optimizing compilers have become an essential component of modern high-performance computer systems. In addition to translating the input program into machine language, they analyze it and apply various transformations to it to reduce its running time or its size. As optimizing compilers become more effective, programmers can become less concerned about the details of the underlying machine architecture and can employ higher-level, more succinct, and more intuitive programming constructs and program organizations.