hpc notes on Models: SIMD, MIMD, SIMT, SPMD, Data Flow Models
There are several models of parallel computing that are commonly used in high-performance computing and other applications. These include:
Single Instruction, Multiple Data (SIMD): In the SIMD model, multiple processors or processing elements execute the same instruction on different pieces of data simultaneously. This model is often used in applications such as image and video processing, where the same operations need to be performed on large amounts of data.
Multiple Instruction, Multiple Data (MIMD): In the MIMD model, multiple processors or processing elements execute different instructions on different pieces of data simultaneously. This model is often used in applications such as scientific simulations and numerical modeling, where different computations need to be performed on different parts of the data.
Single Instruction, Multiple Thread (SIMT): The SIMT model is similar to SIMD, but is used in graphics processing units (GPUs) and other specialized processors. In this model, multiple threads execute the same instruction on different pieces of data simultaneously.
Single Program, Multiple Data (SPMD): In the SPMD model, multiple processors or processing elements execute the same program on different pieces of data simultaneously. This is similar to the MIMD model, but with a single program running on all processors.
Data Flow Models: Data flow models are a type of parallel computing model that emphasizes the flow of data through a system. In this model, each processing element receives data from one or more other elements, performs some computation, and then sends the result to one or more other elements. This model is often used in signal processing, image processing, and other applications that require complex data manipulation.
Overall, each of these models has its own strengths and weaknesses, and the choice of model will depend on the specific application and the underlying hardware architecture.
