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Based on increasing processor word size, allowing simultaneous processing of multiple bits. Example: a 64-bit processor working with 64 bits of data at a time, compared to a 32-bit processor.

Parallelism that results from using specialized hardware, like GPU, to perform certain tasks more efficiently. Example: using a GPU to simultaneously process multiple pixels in an image.

Involves the simultaneous execution of different processes on a system. Example: running multiple applications on different CPU cores simultaneously.

Uses vector instructions to perform the same operation on large sets of data simultaneously. Example: SIMD (Single Instruction, Multiple Data) operations on a vector processor.

Aims to execute multiple instructions from a single program at the same time. Example: a CPU executing multiple assembly instructions in parallel through pipelining.

Involves performing the same operation on different pieces of distributed data simultaneously. Example: applying a function to every element of an array across multiple processors.

Consists of decomposing a task into subtasks and executing them concurrently. Example: running different algorithms on separate processors at the same time.