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In computer architecture, speedup is a number that measures the relative performance of two systems processing the same problem. More technically, it is the improvement in speed of execution of a task executed on two similar architectures with different resources.
According to the law, even with an infinite number of processors, the speedup is constrained by the unparallelizable portion. In computer architecture, Amdahl's law (or Amdahl's argument [1]) is a formula that shows how much faster a task can be completed when you add more resources to the system. The law can be stated as:
Through its memory-bounded function, W=G(M), it reveals the trade-off between computing and memory in algorithm and system architecture design. All three speedup models, Sun–Ni, Gustafson, and Amdahl, provide a metric to analyze speedup for parallel computing. Amdahl’s law focuses on the time reduction for a given fixed-size problem.
In computer architecture, Gustafson's law (or Gustafson–Barsis's law [1]) gives the speedup in the execution time of a task that theoretically gains from parallel computing, using a hypothetical run of the task on a single-core machine as the baseline.
If exactly 50% of the work can be parallelized, the best possible speedup is 2 times. If 95% of the work can be parallelized, the best possible speedup is 20 times. According to the law, even with an infinite number of processors, the speedup is constrained by the unparallelizable portion. Assume that a task has two independent parts, A and B.
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NEW YORK (Reuters) -Donald Trump may seek dismissal of the criminal case in which he was convicted in May of 34 felony counts involving hush money paid to a porn star, a judge ruled on Friday ...
Single instruction, multiple data. Single instruction, multiple data (SIMD) is a type of parallel processing in Flynn's taxonomy.SIMD can be internal (part of the hardware design) and it can be directly accessible through an instruction set architecture (ISA), but it should not be confused with an ISA.