Published: 21 Aug 2025 | Reading Time: 4 min read
Operating systems introduce parallel operation systems to fulfil the increasing demands for fast and efficient computation brought about by advancements in areas like multicore processors and distributed systems. Traditional operating systems were single-threaded and found it hard to deal with modern applications' increasing complexities and scales. Parallel operating systems allow several tasks to work in parallel on several processors, enhancing performance, resource utilisation, and efficiency at the system level. This is ideal for situations like scientific simulations, large-scale data processing, and real-time systems in which speed and accuracy are essential.
A Parallel Operating System is defined as an operating system that controls and coordinates the operations of several processors or computers that function together to perform simultaneous computation. With parallel operating systems, programs are broken into smaller pieces (tasks) that can be executed simultaneously on separate processors or computers (cluster-connected). The system provides help in environments involving multiple processors in one machine or subsequent machines in separate clusters.
Parallel operating systems partition computational tasks into small sub-tasks that must be run simultaneously by assigning these smaller tasks to separate processors. Since an operation can take place on parallel I/O, compared to serial processing (traditional one-at-a-time for each task), the processing and communication of Einstein's theory can be much faster. All the processors connect with each other for the purpose of synchronisation and coordination of tasks, providing for better resource utilisation.
Parallel systems can perform multiple I/O operations at once, thus increasing throughput and reducing project completion time, unlike serial processing. Parallel OS enables speed-ups of time-consuming operations by taking advantage of multi-core processors or clusters of machines, compared to the single-core conventional ones.
There are two primary types of parallel operating systems:
Parallel operating systems are used across many areas needing intensive computing and fast execution of complex tasks. Key applications include:
Several parallel operating systems are available for various purposes:
These systems allow numerous virtual machines with their applications to operate simultaneously: the CPU and RAM become shared resources while not bothering other machines with their operation, thus increasing performance and efficient use of resources.
Parallel operating systems carry out several vital functions to efficiently manage parallel computing systems:
Parallel operating systems are very beneficial since they are used mostly in high-processing and scalable environments:
Despite their benefits, parallel operating systems have several limitations:
A distributed system is a communicative network of mechanical computers working together to achieve a common goal. Today, these computers are often located in various geographical positions and interact with one another over the network while sharing resources. Each node comprises its memory, operates independently, and works collaboratively to process tasks and share data. Any distributed system should be scalable, fault-tolerant, and highly available, typically used in cloud computing, web service, and large-scale data processing applications.
Understanding the key differences between parallel operating systems and distributed systems:
| Aspect | Parallel Operating System | Distributed System |
|---|---|---|
| Architecture | Multiple processors or cores within a single or closely linked machine and network. | Multiple computers are made interoperable through a network. |
| Task Execution | A task is divided between multiple processors, with simultaneous execution on all processors. | A task is done on various computers, proceeding independently. |
| Performance | It is faster because of more effective execution through parallelism. | It's slower due to latency rates with communication and execution in isolation. |
| Memory | Collections of shared memory across processors. | Every computer works in its local memory. |
| Coupling | Tightly coupled systems, where associated processors can communicate close to each other. | Loosely coupled systems where communication is via a network. |
| Synchronization | A global clock coordinates processes operated on processors. | No-global clock, which applies synchronisation algorithms. |
| Examples | Supercomputers and high-performance Computing Clusters. | Cloud computing, Google Cloud, and Amazon Web Services (AWS). |
| Communication | Communication among the processors is performed using shared memory. | Communication would again occur through network links, such as these high-speed buses or a telephone line. |
In conclusion, parallel operating systems aim to enhance performance by breaking tasks into smaller parts that can be executed simultaneously. They play a crucial role in fields that require large-scale computations, including data mining, scientific simulations, and real-time systems. There are many types of parallel systems, including bare-metal and hosted hypervisors. Parallel systems facilitate process management by enhancing processing speed and resource utilisation. However, complexity, cost, and power consumption must be considered before implementation.
Examples are supercomputers such as IBM Blue Gene and Beowulf clusters, where many processors work in parallel to perform complex calculations.
Parallel operation is when multiple tasks are executed simultaneously across several processors to accelerate computations and improve performance.
There are two types of parallel systems:
Multiprocessor Systems: In a multiprocessor system, several processors have shared memory and are closely tied together in executing various tasks. Example: Supercomputers.
Multicomputer Systems: Independent systems connected using a network through a communication medium, where each processor has its assigned memory. Example: Beowulf clusters.
Source: NxtWave CCBP Blog
Original URL: https://www.ccbp.in/blog/articles/parallel-operating-system