Transitioning from structural to nominal code with efficient gradual typing

Gradual typing is a principled means for mixing typed and untyped code. But typed and untyped code often exhibit different programming patterns. There is already substantial research investigating gradually giving types to code exhibiting typical untyped patterns, and some research investigating gradually removing types from code exhibiting typical typed patterns. This paper investigates how to extend these established gradual-typing concepts to give formal guarantees not only about how to change types as code evolves but also about how to change such programming patterns as well. In particular, we explore mixing untyped "structural" code with typed "nominal" code in an object-oriented language. But whereas previous work only allowed "nominal" objects to be treated as "structural" objects, we also allow "structural" objects to dynamically acquire certain nominal types, namely interfaces. We present a calculus that supports such "cross-paradigm" code migration and interoperation in a manner satisfying both the static and dynamic gradual guarantees, and demonstrate that the calculus can be implemented efficiently.

Software code migration strategy from monolithic architecture to microservices

The purpose of this work is to describe a strategy that can help enterprises transition from a monolithic application code architecture to a microservice architecture. Using this migration strategy, the new system will receive a number of pre-assets offered by the microservice architecture, such as scalability and repairability. Companies will be able to migrate their older systems to more flexible systems, while increasing the performance of their software.

Problems and ways of their solving while migration to the new c programming language version

Migration is an actual issue in software engineering. Need of migration appears when updates of languages, libraries, frameworks and more perfect tools come out. The more narrow task of migration is code migration, which means migration from the current programming language to another programming language. Code migration on actual programming language allows to avoid vulnerabilities of earlier vertions, errors (fixed in new programming language version), increase the speed and efficiency of work of the code. However, this task is hard and nowadays there are not enough tools, that allow to migrate from one programming language to another in automatic mode or even facilitate this process. This article describes code migration from the old C programming language version C89/C99 to the new C programming language version C11-C17/C23 and prototyping the transcompiler.

Partial wave analysis with OpenAcc

Partial wave analysis(PWA) is an important tool in hadron physics. Large data sets from the experiments in high precision frontier require high computational power. To utilize GPU cluster and the resource of super computers with various types of accelerator, we implement a software framework for partial wave analysis using OpenAcc, OpenAccPWA. OpenAccPWA provides convenient approaches for exposing parallelism in the code and excellent support for the large amount of existing CPU-based codes of partial wave amplitudes. It can avoid heavy workload of code migration from CPU to GPU. This proceeding will briefly introduce the software framework and performance of OpenAccPWA.

A run control framework to streamline profiling, porting, and tuning simulation runs and provenance tracking of geoscientific applications

Geoscientific modeling is constantly evolving, with next-generation geoscientific models and applications placing large demands on high-performance computing (HPC) resources. These demands are being met by new developments in HPC architectures, software libraries, and infrastructures. In addition to the challenge of new massively parallel HPC systems, reproducibility of simulation and analysis results is of great concern. This is due to the fact that next-generation geoscientific models are based on complex model implementations and profiling, modeling, and data processing workflows. Thus, in order to reduce both the duration and the cost of code migration, aid in the development of new models or model components, while ensuring reproducibility and sustainability over the complete data life cycle, an automated approach to profiling, porting, and provenance tracking is necessary. We propose a run control framework (RCF) integrated with a workflow engine as a best practice approach to automate profiling, porting, provenance tracking, and simulation runs. Our RCF encompasses all stages of the modeling chain: (1) preprocess input, (2) compilation of code (including code instrumentation with performance analysis tools), (3) simulation run, and (4) postprocessing and analysis, to address these issues. Within this RCF, the workflow engine is used to create and manage benchmark or simulation parameter combinations and performs the documentation and data organization for reproducibility. In this study, we outline this approach and highlight the subsequent developments scheduled for implementation born out of the extensive profiling of ParFlow. We show that in using our run control framework, testing, benchmarking, profiling, and running models is less time consuming and more robust than running geoscientific applications in an ad hoc fashion, resulting in more efficient use of HPC resources, more strategic code development, and enhanced data integrity and reproducibility.