Give your career and resume a quality boost by incorporating the latest knowledge in Parallel and Distributed Computing into your work”

A strong advanced knowledge of Parallel and Distributed Computing can significantly boost the career path of any computer scientist who wants to be distinguished. Given the complexity and diverse range of applications in Parallel and Distributed Computing, TECH has entrusted a team of experts to prepare all the program's content.

Therefore, computer scientists will encounter topics dedicated to communication and coordination in computer systems, the analysis and programming of parallel algorithms, and distributed systems in computing, among other pertinent subjects. This content is written with a modern and innovative perspective, leveraging the accumulated experience of the teaching staff.

Thus, computer scientists who complete this program have a decisive advantage in projecting their careers towards the development of applications or systems in the fields of: climate, health, big data, cloud computing or blockchain. Furthermore, given the advanced nature of the syllabus, students have the opportunity to pursue a research project in the field of computer science or other related areas.

Moreover, the program is offered entirely online, eliminating the need for physical attendance in classes and removing the constraints of a predetermined schedule. Computer scientists have the freedom to distribute the course load according to their individual interests, enabling them to strike a balance between studying for their Master's degree and managing their personal or professional responsibilities.

Enroll now to explore the latest developments in Parallel Computing in cloud environments and Distributed Computing-oriented programming”

This professional master’s degree in Parallel and Distributed Computing contains the most complete and up-to-date program on the market. The most important features include:

• The program includes the development of practical cases presented by experts in Parallel and Distributed Computing.The contents are created with graphics, schematics, and practical examples, providing relevant information on the disciplines that are essential for professional practice
• The program includes practical exercises that allow the self-assessment and facilitate the learning process
• The program places a special emphasis on innovative methodologies
• The program incorporates a combination of theoretical lessons, expert-led discussions, and individual reflection work
• The program offers content that is accessible from any fixed or portable device with an Internet connection

You will receive guidance throughout the program from the teaching team, consisting of professionals with extensive experience in Parallel and Distributed Computing”

The program's teaching staff comprises professionals from the sector who bring their valuable work experience to the program. In addition, renowned specialists from leading societies and prestigious universities are also part of the teaching team.

The program offers multimedia content developed using the latest educational technology. This content provides professionals with a contextual and situated learning environment. Through simulated environments, professionals can engage in immersive education that prepares them for real-life situations.

The design of this program focuses on Problem-Based Learning, in which professionals must try to solve the different professional practice situations that are introduced to them throughout the academic year.To facilitate the learning process, students will be supported by an innovative interactive video system developed by renowned and experienced experts.

As a student, you will receive comprehensive support from TECH, the world's largest online academic institution. You will have access to the latest educational technology"

Do not miss the opportunity to be distinguished and able to demonstrate your passion for the present and future of IT"

Acknowledging the rapid advancement of computing, professionals in the field must continuously make efforts to stay updated. In recognition of this need, TECH has developed this program with a specific focus on the latest advancements in Parallel and Distributed Computing. By enrolling in this program, students will not only gain advanced skills in Parallel and Distributed Computing, but they will also explore the diverse applications of today's technologies, including blockchain and cloud computing.

You can accomplish your goal of professional improvement by utilizing the valuable computer tips and insights you will gain from this program”

General Objectives

• Analyze the difference between the different components of Parallel and Distributed Computing
• Measure and compare the efficiency of various components utilized in the system to analyze their performance
• Conduct a comprehensive analysis of Multiplatform Parallel Computing to leverage task-level parallelism among different hardware accelerators
• Analyze in detail current software and architectures
• Delve deeply into the most significant aspects of Parallel and Distributed Computing, expanding your understanding and expertise in the field
• Specialize the students in the application of Parallel and Distributed Computing within diverse industry sectors

Specific Objectives

Module 1. Parallelism in Parallel and Distributed Computing

• Analyzing the processing components: processor or memory
• Deepen the architecture of parallelism
• Analyze the different forms of parallelism from the processor's point of view

Module 2. Parallel Decomposition in Parallel and Distributed Computing

• Analyze the significance of parallel process decomposition in addressing computational problems
• Examine various examples that illustrate the application and utilization of computing, along with its parallel decomposition
• Present methodologies and tools that enable the execution of parallel processes, aiming to achieve optimal performance in parallel computing
• Acquire specialized knowledge to identify scenarios for parallel process decomposition and effectively choose and apply appropriate tools for each specific scenario

Module 3. Communication and Coordination in Computing Systems

• Analyze the different architectures and models of distributed systems
• Determine the characteristics of parallel and distributed systems
• Explore the various types of communications that take place at the process level, examining their characteristics and implications
• Explore diverse communication approaches, such as remote, flow-oriented, message-oriented, and multicast communications, examining their unique characteristics and applications
• Identify emerging types of communications along with their strengths and limitations
• Develop the processes to be followed in selecting algorithms for name service, clock synchronization, coordination, and agreement between system elements
• Compile scenarios that utilize various types of communication technologies to enhance performance and scalability

Module 4. Analysis and Programming of Parallel Algorithms

• Analyze the different parallel programming paradigms
• Examine the most advanced tools to carry out parallel programming
• Analyze parallel algorithms designed for fundamental problems, examining their efficiency, scalability, and applicability
• Specify the design and analysis of parallel algorithms
• Develop parallel algorithms and implement them using popular frameworks such as MPI, OpenMP, and OpenCL/CUDA

Module 5. Parallel Architectures

• Analyze the main computer architectures
• Deepen in key aspects such as process, service and execution thread
• Manage running processes in an operating system
• Use classes to launch and manage processes

Module 6. Parallel Performance

• Analyze the aspects of parallel algorithms that impact their performance and scalability
• Establish the primary metrics for evaluating the performance and scalability of parallel algorithms
• Examine the main techniques for comparing parallel algorithms
• Identify the limitations and constraints imposed by hardware resources on the process of parallelization
• Determine the best practices for optimizing performance in shared memory parallel programs, message passing parallel programs, hybrid parallel programs, and parallel programs with heterogeneous computing
• Compile the most advanced tools for analyzing the performance of parallel algorithms
• Introduce the primary patterns of parallel processing
• Specify a robust procedure for defining high-performance parallel programs

Module 7. Distributed Systems in Computing

• Develop the key elements of a Distributed System
• Examine the applied security elements in Distributed Systems and their necessity
• Present the most commonly used types of Distributed Systems, including their characteristics, functionalities, and the problems they aim to solve
• Provide a proof of the CAP theorem and its applicability to distributed systems. Consistency Availability Partition Tolerance

Module 8. Parallel Computing Applied to Cloud Environments

• Develop the Cloud Computing Paradigm
• Identify the different approaches based on the level of automation and service in distributed systems
• Analyze the main pieces of a cloud architecture
• Establish the differences with an architectureOn-Premise
• Analyze the various deployment options of distributed systems.Cloud: Multi-Cloud, Hybrid Cloud
• Explore the inherent benefits of cloud computing
• Discuss the principles of cloud computing economics, including the transition from CAPEX to OPEX
• Evaluate the commercial offer of the different suppliers Cloud
• Assess the capabilities of cloud computing for supercomputing
• Examine the topic of security in cloud computing

Module 9. Models and Formal Semantics. Examine programming approaches focused on distributed computing

• Identify the benefits of formal semantics
• Explore the ways in which formal semantics can aid in programming for distributed computing
• Specify the potential applications of formal semantics in the context of programming for distributed computing
• Delve deeply into the key tools and techniques that assess the feasibility of projects utilizing distributed computing technology
• Identify programming languages that operate within the semantic model
• Determine how this semantic models help us with the programming languages
• Evaluate and compare computing models
• Specify the practical application of distributed models
• Introduce cutting-edge market tools for project implementation

Module 10. Parallel and Distributed Computing Applications

• Demonstrate the great contribution of Parallel and Distributed Computing applications to our environment
• Identify the reference architectures in the market
• Evaluate the advantages of this cases
• Present successful solutions in the market
• Demonstrate why is it important for assessing climate change
• Determine the current importance of GPUs
• Present the impact of this technology on power grids
• Explore distributed engines to serve your potential future customers
• Explore the advantages of distributed computing engines and see how they be beneficial for a company
• Provide examples of in-memory databases and highlight their significance
• Explore how these models contribute to the field of medicine

You will embark on a comprehensive journey covering the most important aspects of Parallel and Distributed Computing, ranging from inherent parallelisms to their diverse applications”