More precisely, and attending to our objectives, we analyze the gains of F l u χ with dataflows for continuous and incremental processing in terms of: i) result convergence, as the dataflow execution pipeline advances; ii) error coverage; and iii) machine loads and resource usage through the amount of executions performed/saved.
These instructions could be scheduled to execute in parallel, but a modern CPU has a limited number of functional units, therefore limiting the amount of parallel execution.
For example, "Guest shall pay to Homeowner a deposit in the amount of $500 due upon execution of this Agreement, and then $1150 on the 1st day of each month, beginning on June 1 , 2009 and ending on September 1 , 2009
In conventional architectures, the central processing unit (CPU) spends a significant amount of execution time allocating and de-allocating memory.
In general, this method requires an important amount of execution time to provide results, depending on the detail of the simulation model.
We first formulate an integer programming optimization model for the embedding problem that minimizes the amount of bandwidth required for workflow execution.
More specifically, in [23], they minimize the workload's makespan while in [24], they focus on maximizing a profit metric which depends on the amount of jobs that satisfy their execution time deadlines.
The reason for this can be attributed to the LIGO workload comprising jobs with higher average execution times compared to those of the CyberShake workload, as well as the values of s max used not significantly reducing the amount of jobs that have overlapping execution times (i.e., not reducing the contention for resources).
It consists in selecting a minimal set of test cases from a large test suite, ensuring that the test cases selected cover a given set of requirements of a piece of software at the same time as it minimizes the amount of resources required for its execution.
In this study we find that there is a relationship between the amount of noise present in action execution and the coarseness of the sensory representation: more noise leads to larger states (see, e.g. figure 7).
