How can you compare shared-memory and distributed-memory architectures?

1 Shared-memory architecture

A shared-memory architecture is a system where all the processors or nodes have access to a common memory pool. This means that they can read and write data to the same memory locations, and share information through shared variables. The advantage of this architecture is that it simplifies the programming model, as the programmers do not need to explicitly manage the data transfer or synchronization among the processors. The disadvantage is that it can cause contention and scalability issues, as the processors compete for the memory access and bandwidth, and the memory size limits the number of processors.

2 Distributed-memory architecture

A distributed-memory architecture is a system where each processor or node has its own local memory, and they communicate with each other through message passing. This means that they can only access their own memory locations, and exchange information through sending and receiving messages. The advantage of this architecture is that it avoids the contention and scalability problems of the shared-memory architecture, as the processors do not interfere with each other's memory access and bandwidth, and the memory size does not limit the number of processors. The disadvantage is that it complicates the programming model, as the programmers need to explicitly manage the data distribution and communication among the processors.

3 Hybrid architecture

A hybrid architecture is a system that combines the features of both shared-memory and distributed-memory architectures. It is typically composed of several clusters or nodes, each with multiple processors that share a local memory, and they communicate with other clusters or nodes through message passing. This means that they can exploit the benefits of both architectures, such as the ease of programming within a cluster and the scalability across clusters. The challenge of this architecture is to balance the trade-off between the communication cost and the computation efficiency.

4 Performance metrics

To compare the performance of different architectures, some common metrics are used, such as speedup, efficiency, and scalability. Speedup measures how much faster a parallel system can solve a problem than a sequential system. Efficiency measures how well the parallel system utilizes the available resources. Scalability measures how the parallel system adapts to the changes in the problem size or the number of processors. These metrics can help evaluate the suitability of an architecture for a given problem and optimize the design of a parallel system.

5 Application domains

Different architectures are suited for different application domains, depending on the characteristics of the problems and the requirements of the solutions. For example, shared-memory architectures are often used for problems that involve frequent and irregular data access, such as graph algorithms, machine learning, and image processing. Distributed-memory architectures are often used for problems that involve large and regular data sets, such as numerical simulations, scientific computing, and big data analytics. Hybrid architectures are often used for problems that involve both types of data access patterns, such as web search, social network analysis, and natural language processing.

6 Future trends

The future trends of parallel and distributed computing are likely to involve more diverse and heterogeneous architectures, such as cloud computing, edge computing, and quantum computing. These architectures pose new challenges and opportunities for the programmers and researchers, such as how to deal with the variability, uncertainty, and complexity of the systems, how to leverage the potential of the novel technologies, and how to address the ethical and social implications of the applications.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?