Примери коришћења Parallel computing на Енглеском и њихови преводи на Српски
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Parallel Computing.
What is Parallel Computing?
It takes better advantage of Parallel Computing.
We promised parallel computing benchmarks lately. Here we go….
Even though the processing power expressed by DNA flips is low,the high number of bacteria in a culture provides a large parallel computing platform.
Parallel Computing, also called Multitasking is when a software executes more then 1 task at a time.
There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism.
In parallel computing, all processors may have access to a shared memory to exchange information between processors.
The ARC and VAXcluster products not only supported parallel computing, but also shared file systems and peripheral devices.
For example, parallel computing, there are many possible models typically reflecting different ways processors can be interconnected.
Fields as varied as bioinformatics(for protein folding and sequence analysis) and economics(for mathematical finance) have taken advantage of parallel computing.
It is used in parallel computing to predict theoretical maximum speed up using multiple processors.
With the end of frequency scaling, these additional transistors(which are no longer used for frequency scaling)can be used to add extra hardware for parallel computing.
It is often used in parallel computing to predict the theoretical speedup when using multiple processors.
For example, if 90% of the program can be parallelized,the theoretical maximum speed-up using parallel computing would be 10x no matter how many processors are used.
It is often used in parallel computing to predict the theoretical maximum speedup using multiple processors.
For example, if 95% of theprogram can be parallelized, then the theoretical maximum speedup using parallel computing would be 20 times faster, no matter how many processors are used.".
The terms"concurrent computing","parallel computing", and"distributed computing" have a lot of overlap, and no clear distinction exists between them.
This includes well-equipped laboratories, a suite of electron microscopes, a confocal scanning microscope and a protein and DNA analytical service andadvanced super and parallel computing facilities.
There can be different forms of parallel computing like bit-level, instruction-level, data and task-parallelism.
The FGCS Project was a $400M initiative by Japan's Ministry of International Trade and Industry, begun in 1982,to use massively parallel computing/processing for artificial intelligence applications.
Parallel computing is used in a wide range of fields, from bioinformatics(protein folding and sequence analysis) to economics(mathematical finance).
Without going into too many details,Quantum CSS uses parallel computing and other improvements to make the handling of CSS in Firefox a lot faster.
Parallel computing Mainstream parallel programming languages remain either explicitly parallel or(at best) partially implicit, in which a programmer gives the compiler directives for parallelization.
For example, if 95% of the program can be parallelized,the theoretical maximum speedup using parallel computing would be 20× as shown in the diagram, no matter how many processors are used.
Skip lists are also useful in parallel computing, where insertions can be done in different parts of the skip list in parallel without any global rebalancing of the data structure.
The concept of concurrent computing is frequently confused with the related butdistinct concept of parallel computing, although both can be described as"multiple processes executing during the same period of time".
In parallel computing, execution occurs at the same physical instant: for example, on separate processors of a multi-processor machine,with the goal of speeding up computations- parallel computing is impossible on a(one-core) single processor, as only one computation can occur at any instant(during any single clock cycle).
In computing, MISD(multiple instruction, single data)is a type of parallel computing architecture where many functional units perform different operations on the same data.
In a narrow sense,HPC mainly includes parallel computing and cluster computing, which are used in high-tech simulation, computing and so on.