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