Cost efficiency

Short description: Computer algorithms, refers to a measure of how effectively parallel computing can be used

Cost efficiency (or cost optimality), in the context of parallel computer algorithms, refers to a measure of how effectively parallel computing can be used to solve a particular problem. A parallel algorithm is considered cost efficient if its asymptotic running time multiplied by the number of processing units involved in the computation is comparable to the running time of the best sequential algorithm.

For example, an algorithm that can be solved in O(n) time using the best known sequential algorithm and O(np) in a parallel computer with p processors will be considered cost efficient.

Cost efficiency also has applications to human services.

## References

* Advanced Computer Architectures: A Design Space Approach, D. Sima, T. Fountain and P. Kacsuk, Addison-Wesley, 1997.

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Parallel computing

General|

* Distributed computing
* Parallel computing
* Massively parallel
* Cloud computing
* High-performance computing
* Multiprocessing
* Manycore processor
* GPGPU
* Computer network
* Systolic array

Levels|

* Bit
* Instruction
* Thread
* Task
* Data
* Memory
* Loop
* Pipeline

Multithreading|

* Temporal
* Simultaneous (SMT)
* Speculative (SpMT)
* Preemptive
* Cooperative
* Clustered Multi-Thread (CMT)
* Hardware scout

Theory|

* PRAM model
* PEM Model
* Analysis of parallel algorithms
* Amdahl's law
* Gustafson's law
* Cost efficiency
* Karp–Flatt metric
* Slowdown
* Speedup

Elements|

* Process
* Thread
* Fiber
* Instruction window
* Array data structure

Coordination|

* Multiprocessing
* Memory coherency
* Cache coherency
* Cache invalidation
* Barrier
* Synchronization
* Application checkpointing

Programming|

* Stream processing
* Dataflow programming
* Models
* Implicit parallelism
* Explicit parallelism
* Concurrency
* Non-blocking algorithm

Hardware|

* Flynn's taxonomy
* SISD
* SIMD
* SIMT
* MISD
* MIMD
* Dataflow architecture
* Pipelined processor
* Superscalar processor
* Vector processor
* Multiprocessor
* symmetric
* asymmetric
* Memory
* shared
* distributed
* distributed shared
* UMA
* NUMA
* COMA
* Massively parallel computer
* Computer cluster
* Grid computer
* Hardware acceleration

APIs|

* Ateji PX
* Boost.Thread
* Chapel
* HPX
* Charm++
* Cilk
* Coarray Fortran
* CUDA
* HIP
* Dryad
* C++ AMP
* Global Arrays
* MPI
* OpenMP
* OpenCL
* OpenHMPP
* OpenACC
* TPL
* PLINQ
* PVM
* POSIX Threads
* RaftLib
* UPC
* TBB
* ZPL

Problems|

* Automatic parallelization
* Deadlock
* Livelock
* Deterministic algorithm
* Embarrassingly parallel
* Parallel slowdown
* Race condition
* Software lockout
* Scalability
* Starvation

* Category: parallel computing
* Media related to Parallel computing at Wikimedia Commons

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