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Software and Computing

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Software and computing are integral to driving innovation and developing resilient infrastructure. They enable the design, development, and management of digital infrastructure and systems, including communication networks, data centers, and smart cities. Software innovation also supports industrial automation, optimization, and efficiency. Software and computing are essential for building sustainable cities and communities. They contribute to urban planning, resource management, energy efficiency, and the implementation of smart city technologies. Software applications also enhance citizen engagement, promote inclusive governance, and support the development of sustainable urban solutions. Software and computing have a crucial role in addressing climate change. They enable the collection, analysis, and modeling of climate data, facilitating climate research and informing policy decisions. Additionally, software solutions support energy management, carbon footprint monitoring, and the development of sustainable technologies.

Science and Technology

Description of Subtheme:

Software and Computing includes the study and implementation of algorithmic processes, coding, machine learning, database, and security. Research in Software Computing includes applications in scientific, engineering, mathematical, and social aspects.

  1. Parallel Processing

Parallel computing is concerned with using both software and hardware approaches and techniques to accelerate the execution of computer programs run on all types of computers, ranging from small held devices to supercomputers. This investigates the use of multi-core processors, the main stream in processor design, to exploit many types of parallelism in applications. Specifically, the study is centered on how to restructure common algorithms in image processing and data encryption/description to exploit the three main degrees of parallelism, namely, data-level, instruction-level, and task-level parallelism.

  1. Cloud Computing

Develop energy-efficient algorithms for allocating and scheduling application tasks on cloud computing platforms. Nowadays, cloud computing is the standard de-facto in computing systems, it offers computing as a service. Instead of purchasing hardware and software infrastructures. However, running applications on these systems demand good management to maximize revenue for providers reduce energy consumption, and satisfying quality-of-service requirements for users. Undergoing work is mainly focused on designing application-aware and energy-aware algorithms for scheduling application tasks on cloud systems.

  1. Artificial Intelligence

Artificial Intelligence (AI) is a dynamic field in computer science focused on creating intelligent machines that emulate human cognitive functions. Key areas within AI include Machine Learning, where computers learn from data for applications like medical diagnosis and fraud detection. Image processing involves manipulating visual data with mathematical operations, aiding in tasks like medical imaging and facial recognition, etc.