Although the curve fitting can be done in real time, the time to create the learning curve depends on the classification task, batch size, feature number, processing time of the machine among others.
We demonstrate these principles using the NIST LRE 2003 standard LID task, a batch processing task which involves the analysis of over 600 h of speech.
In the single-channel task, full batch processing reduced word error rate (WER) from 10.0 to 9.3 % on SimData as compared to utterance-based batch processing.
In order to model our example the following events have been chosen: E 0 : job starts to copy input data from workstation to HPC cluster, E 1 : job submits computing task to batch queuing system, E 2 : computing task is scheduled and starts execution, E 3 : computing task is finished and job starts copying result data from HPC cluster to workstation, E 4: job has finished copying the results data.
It also provides the ability to run different types of tasks than batch-oriented MapReduce jobs.
As the availability of sequence data increases, more researchers are downloading the BLAST program for local installation and performing larger and more complex tasks, including batch queries.
To produce a batch in a batch plant, equipment assignments to each task of a batch are carried out on the basis of the equipment requirement information, of the master recipe.
The Charniak Johnson parser takes about 10 s to load the parsing model files and, in order for this fixed time penalty not to accumulate, it is necessary to divide the parsing task to large batches rather than parsing a single abstract, or even single sentence at a time.
Consider batching tasks like that into one session per day.
A MapReduce job initiates long-lived batch tasks running on Slave nodes, which usually take a few minutes or hours.
