Questions tagged [parallelism-amdahl]

Amdahl's law, also known as Amdahl's argument, is used to find the maximum expected improvement to an overall system when only part of the system is improved. It is often used in parallel computing to predict the theoretical maximum speedup using multiple processors. The law is named after computer architect Gene Amdahl, and was presented at the AFIPS Spring Joint Computer Conference in 1967.

Amdahl's law, also known as Amdahl's argument, is used to find the maximum expected improvement to an overall system when only part of the system is improved. It is often used in to predict the theoretical maximum speedup using multiple processors. The law is named after computer architect Gene Amdahl, and was presented at the AFIPS Spring Joint Computer Conference in 1967.

The speedup of a program using multiple processors in parallel computing is limited by the time needed for the sequential fraction of the program. For example, if a program needs 20 hours using a single processor core, and a particular portion of the program which takes one hour to execute cannot be parallelized, while the remaining 19 hours (95%) of execution time can be parallelized, then regardless of how many processors are devoted to a parallelized execution of this program, the minimum execution time cannot be less than that critical one hour. Hence the speedup is limited up to 20x.

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What is the performance of 100 processors capable of 2 GFLOPs running 2% sequential and 98% parallelizable code?

This is how I solved the following question, I want to be sure if my solution is correct? A multiprocessor consists of 100 processors, each capable of a peak execution rate of 2 Gflops. What is the performance of the system as measured in Gflops…
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Evaluating methods in parallel

Let's say I need the output from the below independent methods var x = LongCalculation(123) var y = LongCalculation2(345) var z = LongCalculation3(678) var b = LongCalculation4(910) What is the least code invasive way of executing these…
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Very slow example parallel code in python, slower then serial

I am trying to learn parallel programming with python 3 and have troubles with all the toy examples. Particularly, get any code from textbook/course/youtube, try to execute it and... get very slow working. I've actually never seen fast working…
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How to call same function in parallel with executor service in JAVA?

I am new to concurrency and threading in java and I have this following scenario - Function1(fetches next task from a queue and calls function2 with task) then Function2(calls Function Run to run this task) then Run(function run is submiting task…
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What is Gustafson's law trying to argue?

Gustafson's law is a counter to Amdahl's law claiming that most parallel processing applications actually increase the workload when having increased access to parallel processing. Thus, Amdahl's law which assumes constant workload to measure…
Izzo
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Processor Speedup Calculation Difference

I am trying to understand why Amdahl's law does not apply to this situation? Let's say we have two configs Config 1 has L1 access latency (hitDelay and missDelay as 1 cycle) Config 2 has L1 access latency as 7 cycles. Assuming load and store are 30%…
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Should I change my original Python/Tensorflow code to make it run faster on HPC?

Please forgive if this question is too basic. I am neither familiar with the idea of parallelization nor used a HPC system before. I am training a deep learning model which takes really long on my PC. It takes approximately 2 days on my i5 with 12…
Arwen
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Predicting Parallel Performance of Differential Evolution in Python

I am an engineering student doing an internship on genetic algorithms. Lately, I've been making a lot of research on Differential Evolution. With the responsible of my internship we decided to test the Differential Evolution by directly using…
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Parallelize Array Assignments in Python

I have been trying to parallelize the whole function when it is called at main, or, any segments of the function which you see below without luck and it seems that I can't get away with the TypeError: function object is not iterable. Appreciate any…
Amir
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Does the guarantee of non-divergence when dispatching single work item exist?

As we know, work items running on GPUs could diverge when there are conditional branches. One of those mentions exist in Apple's OpenCL Programming Guide for Mac. As such, some portions of an algorithm may run "single-threaded", having only 1 work…
DannyNiu
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How can I use more CPU to run my python script

I want to use more processors to run my code to minimize the running time only. Though I have tried to do it but failed to get the desired result. My code is a very big one that's why I'm giving here a very small and simple code (though it does not…
Photon
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How to run a TensorFlow in parallel with some other processing on Raspberry Pi3

I would like to run a continuous stream with the PiCamera on the Raspberry Pi 3 and also do other computations in parallel with this stream. I only have to take from that stream(process) the object that it detected. I will post here the code I have…
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Find Serial and parallel percentage of code

If I know the job completion time of a 2 processor system and of a 4 processor system, how do i calculate the time taken(Ts) by a 1 processor system. I want to know this so I can find the serial percentage of any given code using the equation Ts/Tp…
kiran
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Speed up without a serial fraction

I ran a set of experiments on a parallel package, say superlu-dist, with different processor numbers e.g.: 4, 16, 32, 64 I got the wall clock time for each experiment, say: 53.17s, 32.65s, 24.30s, 16.03s The formula of speedup is : …
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Parallel programming on a nested for loop in Python using PyCuda (or else?)

Part of my python function looks like this: for i in range(0, len(longitude_aq)): center = Coordinates(latitude_aq[i], longitude_aq[i]) currentAq = aq[i, :] for j in range(0, len(longitude_meo)): currentMeo = meo[j, :] …
gtheo
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