wall clock time


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wall clock time

(software)
The elapsed time between when a process starts to run and when it is finished. This is usually longer than the processor time consumed by the process because the CPU is doing other things besides running the process such as running other user and operating system processes or waiting for disk or network I/O.
This article is provided by FOLDOC - Free Online Dictionary of Computing (foldoc.org)
References in periodicals archive ?
For both matrices we measure wall clock time using the Octave/Matlab tic and toc commands.
When matrix vector products are expensive relative to other arithmetic operations, smaller matrix vector product usage correlates directly with shorter wall clock times. We examine two normalized graph Laplacian matrices [28]: one from a 10,000 x 10,000 synthetic matrix generated using the GRAPHGEN graph generator implementation in SNAP [24] (using the Albert-Barabasi adjacency model [3]), and the other from University of Florida sparse matrix collection [16].
The matrix-vector products and wall clock times are shown in Figure 4.6.
The number of matrix-vector products and the wall clock times are shown in Figure 4.7.
In fact, one can see that the wall clock times for the d := 80 runs are slightly larger than those for d := 40.
With LXI Class A and B, IEEE 1588 ensures that distributed devices have the same notion of wall clock time by establishing which device has the most accurate clock and assigning it as the master while all other devices are designated as slaves.
Total wall clock time for the run was 32m:29.183s, representing a 916X speedup over the 68-node traditional cluster.
You have to do it where it hits so you get better wall clock time. Backups aren't taking the full weekend; they're going down to 15 minutes.
What they all brought up was the wall clock time. They all expected the reduction in data with the commonality factoring.
But you get better wall clock time, better integrity, very efficient replication to remote locations.
(Each PC has 2 GB of RAM, a 2 gigaHertz clock speed, and a 34 GB hard drive.) The operating system was Windows XR Solving ill parallel across all four CPUs, the analysis converged, or solved, within 400 iterations, requiring 20 hours of wall clock time.
Nonlinear analyses of the cube [micro]FE model with geometrical nonlinearities took less than 7.4 hours wall clock time and required 4.1 GB memory.