87 lines
4.2 KiB
Markdown
87 lines
4.2 KiB
Markdown
---
|
|
title: Parallel Computing
|
|
---
|
|
## Parallel Computing
|
|
|
|
In the simplest sense, parallel computing is the simultaneous use of **multiple compute resources** to solve a computational problem:
|
|
- A problem is broken into discrete parts that can be solved concurrently.
|
|
- Each part is further broken down to a series of instructions.
|
|
- Instructions from each part execute simultaneously on different processors.
|
|
- An overall control/coordination mechanism is employed.
|
|
|
|
|
|
|
|
### Why Parallelism
|
|
- Faster, of course
|
|
- Finish the work earlier - Same work in less time
|
|
- Do more work - More work in the same time
|
|
|
|
### How to parallelize
|
|
- Firstly, break down the computational part into small pieces.
|
|
- Then, sssign the small jobs to the parallel running processes.
|
|
- But it might become complicated when the small piece of jobs depend upon others.
|
|
|
|
### Writing a Parallel Program
|
|
- If you are starting with an existing serial program, debug the serial code completely.
|
|
- Identify which parts of the program can be executed concurrently.
|
|
- Requires a thorough understanding of the algorithm.
|
|
- Exploit any parallelism which may exist.
|
|
- May require restructuring of the program and/or algorithm. May require an entirely new algorithm.
|
|
- Decompose the program:
|
|
- Task Parallelism
|
|
- Data Parallelism
|
|
- Combination of both
|
|
|
|
### Task (Functional) Parallelism
|
|
- Different operations are performed on the same or different data in parallel to fully utilize the resources.
|
|
- Decomposing the problem into different processes which can be distributed to multiple processors for simultaneous execution.
|
|
- Good to use when there is not static structure or fixed determination of number of calculations to be performed.
|
|
|
|
### Data (Domain) Parallelism
|
|
- Same operations are performed on different subsets of same data structure.
|
|
- Partitioning the problem's data domain and distributing portions to multiple processors for simultaneous execution.
|
|
- Good to use for problems where:
|
|
- data is static.
|
|
- domain is fixed but computation within various regions of the domain is dynamic.
|
|
|
|
### Elements of a Parallel Computer
|
|
- Hardware
|
|
- Multiple Processors
|
|
- Multiple Memories
|
|
- Interconnection Network
|
|
- System Software
|
|
- Parallel Operating System
|
|
- Programming Constructs to Express/Orchestrate Concurrency
|
|
- Application Software
|
|
- Parallel Algorithms
|
|
|
|
### Communication Model of Parallel Platforms
|
|
- There are two primary forms of data exchange between parallel tasks
|
|
- accessing a shared data space and exchanging messages.
|
|
- Platforms that provide a shared data space are called **shared-address-space** machines or **mult iprocessors**.
|
|
- Platforms that support messaging are called **message passing platforms** or **multicomputers**.
|
|
|
|
### Shared-Address-Space Platforms
|
|
- Part (or all) of the memory is accessible to all processors.
|
|
- Processors interact by modifying data objects stored in this shared-address-space.
|
|
- If the time taken by a processor to access any memory word in the system (global or local) is
|
|
- identical, then the platform is classified as a **uniform memory access (UMA)**,
|
|
- not identical, then its classified as **non-uniform memory access (NUMA)** machine.
|
|
|
|
|
|
|
|
### Message-Passing Platforms
|
|
- These platforms comprise of a set of processors and their own (exclusive) memory.
|
|
- Instances of such a view come naturally from clustered workstations and non-shared-addressspace multicomputers.
|
|
- Interactions between processes running on different nodes must be accomplished using messages.
|
|
- The exchange of messages is used to transfer data, work and to synchronize actions among the processes.
|
|
- These platforms are programmed using (variants of) **send** and **receive** primitives.
|
|
- Libraries such as **MPI** and **PVM** provide such primitives.
|
|
|
|
|
|
|
|
|
|
#### More Information:
|
|
- [Parallel Computing on Wikipedia](https://en.wikipedia.org/wiki/Parallel_computing)
|
|
- [Introduction to Parallel Computing](https://computing.llnl.gov/tutorials/parallel_comp/)
|