Achieve the desired quality improvement by leveraging the knowledge provided by this Postgraduate diploma”

Parallel Computing encompasses a broad range, from the architecture of the systems themselves to the programming of algorithms. It includes the design of hardware devices and the subsequent implementation of software that takes full advantage of this configuration. To secure their place in the best projects and leadership positions, the computer scientist must not only have a deep understanding of one of today's most prevalent programming models but also master it.

Thus, this Postgraduate diploma starts by providing a general overview of what parallelism in Parallel Computing entails. It then delves into the programming of parallel algorithms and concludes with an in-depth analysis of the various types of parallel architectures.

The teaching team has devoted special attention to the development of all the contents of this degree, placing significant emphasis not only on the most advanced theory but also on their own professional experience. The program is thus enriched by the teachers' own contributions, as they adapt all the content of Parallel Computing to the realities of today's labor market.

The 100% online format of the diploma is also noteworthy, as it provides a preferred option for computer scientists who aim to delve deeper into the subject without having to compromise their personal and professional responsibilities. This program is accessible for download on any device with an internet connection, eliminating the need for in-person classes and rigid schedules.

Enroll today in this Postgraduate diploma in Parallel Computing and embark on a journey to uncover all the secrets of multiprocessors and OpenMP. Don't wait any longer to seize this opportunity!”

This Postgraduate diploma in Parallel Computing contains the most complete and up-to-date program on the market. The most important features include:

• The program incorporates the development of case studies that are presented by experts in Parallel Computing
• The program is designed with graphical, schematic, and highly practical content, which gathers essential information about disciplines that are crucial for the professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies
• The program incorporates theoretical lessons, interactive question-and-answer sessions with experts, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

By enrolling in this program, you will gain exclusive access to a diverse array of multimedia resources. These resources include meticulously crafted videos, personally tailored by the professors themselves for each topic covered in the program”

The teaching staff of the program consists of professionals from the industry who bring their valuable work experience to the table. Additionally, renowned specialists from leading societies and prestigious universities contribute their expertise to enrich the program.

The program's multimedia content, created using state-of-the-art educational technology, enables professionals to learn in a contextual and situated learning environment. This simulated environment offers immersive education specifically designed to prepare individuals for real-world situations.

The design of this program places a strong emphasis on Problem-Based Learning. Throughout the academic year, professionals are presented with various real-world practice situations that they must strive to solve, enabling them to apply their knowledge in practical scenarios. For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts.

At TECH, you have the autonomy to make crucial decisions, such as determining when, where, and how to undertake the entire teaching load"

Give your resume a high-quality boost and position yourself advantageously to secure better job positions in your IT career"

The structure and content of this Postgraduate diploma have been meticulously crafted to optimize the study experience for computer scientists, ensuring maximum facilitation and support. Thus, TECH has incorporated the  relearning pedagogical methodology across all subjects, resulting in a significant reduction in the amount of study hours required for this program. This advantage also allows students to allocate more time to specific areas of parallel architecture or algorithm programming that align with their individual interests and priorities.

You will have access to a wide range of audiovisual material, including introductory videos, summaries, in-depth analysis, and motivational videos. These resources comprehensively cover the most relevant aspects of each topic”

Module 1. Parallelism in Parallel and Parallel Computing

1.1. Parallel Processing

1.1.1. Parallel Processing
1.1.2. Parallel Processing in Computing. Purpose
1.1.3. Parallel Processing: Analysis

1.2. Parallel System

1.2.1. The Parallel System
1.2.2. Levels of Parallelism
1.2.3. Parallel System

1.3. Processor Architectures

1.3.1. Processor Complexity
1.3.2. Processor Architecture. Mode of Operation
1.3.3. Processor Architecture. Memory Organization

1.4. Networks in Parallel Processing

1.4.1. Mode of Operation
1.4.2. Control Strategy
1.4.3. Switching Techniques
1.4.4. Topology

1.5. Parallel Architectures

1.5.1. Algorithms
1.5.2. Coupling
1.5.3. Communication

1.6. Performance of Parallel Computing

1.6.1. Performance Evolution
1.6.2. Performance Measures
1.6.3. Parallel Computing. Study Cases

1.7. Flynn's Taxonomy

1.7.1. MIMD: shared memory
1.7.2. MIMD: distributed memory
1.7.3. MIMD: Hybrid systems
1.7.4. Data Flow

1.8. Forms of Parallelism: TLP (Thread Level Paralelism)

1.8.1. Forms of Parallelism: TLP (Thread Level Paralelism)
1.8.2. Coarse grain
1.8.3. Fine grain
1.8.4. SMT

1.9. Forms of Parallelism: DLP (Data Level Paralelism)

1.9.1. Forms of Parallelism: DLP (Data Level Paralelism)
1.9.2. Short Vector Processing
1.9.3. Vector Processors

1.10. Forms of Parallelism: ILP (Instruction Level Paralelism)

1.10.1. Forms of Parallelism: ILP (Instruction Level Paralelism)
1.10.2. Segmented Processors
1.10.3. Superscalar Processor
1.10.4. Very Long Instruction Word (VLIW) Processor

Module 2. Analysis and Programming of Parallel Algorithms

2.1. Parallel Algorithms

2.1.1. Problem Decomposition
2.1.2. Data Dependencies
2.1.3. Implicit and Explicit Parallelism

2.2. Parallel Programming Paradigms

2.2.1. Parallel Programming with Shared Memory
2.2.2. Parallel Programming with Distributed Memory
2.2.3. Hybrid Parallel Programming
2.2.4. Heterogeneous Computing- CPU + GPU
2.2.5. Quantum Computing New Programming Models with Implicit Parallelism

2.3. Parallel Programming with Shared Memory

2.3.1. Models of Parallel Programming with Shared Memory
2.3.2. Parallel Algorithms with Shared Memory
2.3.3. Libraries for Parallel Programming with Shared Memory

2.4. OpenMP

2.4.1. OpenMP
2.4.2. Running and Debugging Programs with OpenMP
2.4.3. Parallel Algorithms with Shared Memory in OpenMP

2.5. Parallel Programming by Message Passing

2.5.1. Message Passing Primitives
2.5.2. Communication Operations and Collective Computing
2.5.3. Parallel Message-Passing Algorithms
2.5.4. Libraries for Parallel Programming with Message Passing

2.6. Message Passing Interface (MPI)

2.6.1. Message Passing Interface (MPI)
2.6.2. Execution and Debugging of Programs with MPI
2.6.3. Parallel Message Passing Algorithms with MPI

2.7. Hybrid Parallel Programming

2.7.1. Hybrid Parallel Programming
2.7.2. Execution and Debugging of Hybrid Parallel Programs
2.7.3. MPI-OpenMP Hybrid Parallel Algorithms

2.8. Parallel Programming with Heterogeneous Computing

2.8.1. Parallel Programming with Heterogeneous Computing
2.8.2. AIH vs. GPU
2.8.3. Parallel Algorithms with Heterogeneous Computing

2.9. OpenCL and CUDA

2.9.1. OpenCL vs. CUDA
2.9.2. Executing and Debugging Parallel Programs with Heterogeneous Computing
2.9.3. Parallel Algorithms with Heterogeneous Computing

2.10. Design of Parallel Algorithms

2.10.1. Design of Parallel Algorithms
2.10.2. Problem and Context
2.10.3. Automatic Parallelization vs. Manual Parallelization
2.10.4. Problem Partitioning
2.10.5. Computer Communications

Module 3. Parallel Architectures

3.1. Parallel Architectures

3.1.1. Parallel Systems. Classification
3.1.2. Sources of Parallelism
3.1.3. Parallelism and Processors

3.2. Performance of Parallel Systems

3.2.1. Performance Metrics and Measurements
3.2.2. Speed-up
3.2.3. Granularity of Parallel Systems

3.3. Vector Processors

3.3.1. Basic Vector Processor
3.3.2. Interleaved or Interleaved Memory
3.3.3. Performance of Vector Processors

3.4. Matrix Processors

3.4.1. Basic Organization
3.4.2. Programming in Matrix Processors
3.4.3. Programming in Matrix Processors. Practical Example

3.5. Interconnection Networks

3.5.1. Interconnection Networks
3.5.2. Topology, Flow Control and Routing
3.5.3. Interconnection Networks. Classification According to Topology

3.6. Multiprocessors

3.6.1. Multiprocessor Interconnection Networks
3.6.2. Memory and Cache Consistency
3.6.3. Probe Protocols

3.7. Synchronization

3.7.1. Bolts (Mutual exclusion)
3.7.2. P2P Synchronization Events
3.7.3. Global Synchronization Events

3.8. Multicomputers

3.8.1. Multicomputer Interconnection Networks
3.8.2. Switching Layer
3.8.3. Routing Layer

3.9. Advanced Architectures

3.9.1. Data Stream Machines
3.9.2. Other Architectures

3.10. Parallel and Distributed Programming

3.10.1. Parallel Programming Languages
3.10.2. Parallel Programming Tools
3.10.3. Design Patterns
3.10.4. Concurrency of Parallel and Distributed Programming Languages

You will have access to the most advanced technological and educational resources that TECH can provide, enhancing your learning experience to the fullest possible extent”