50%
19.05.2014
with my /home/layton
directory on my local system (host = desktop
). I also access an HPC system that has its own /home/jlayton
directory (the login node is login1
). On the HPC system I only keep some
49%
13.10.2020
scales linearly with the number of processors.
Further Exploration
To further understand how Amdahl’s Law works, take a theoretical application that is 80% parallelizable (i.e., 20% cannot
48%
28.08.2013
uses a single core. Sixty-three cores are sitting there idle until the Gzip finishes. Moreover, using a single core to Gzip a file on a 2PB Lustre system that is capable of 20GBps is like draining
48%
25.01.2017
-dimensional array from one-dimensional arrays.
The use of coarrays can be thought of as opposite the way distributed arrays are used in MPI. With MPI applications, each rank or process has a local array; then
47%
10.07.2017
with the original Raspberry Pi Model A, ranging from two to more than 250 nodes. That early 32-bit system had a single core running at 700MHz with 256MB of memory. You can build a cluster of five RPi3 nodes with 20
47%
04.11.2011
of parallel programming. It is always worthwhile to check whether a useful piece of software already exists for the problem. If a program needs the Message Passing Interface (MPI), or is at least capable
46%
12.03.2015
definitely stress the processor(s) and memory, especially the bandwidth. I would recommend running single-core tests and tests that use all of the cores (i.e., MPI or OpenMP).
A number of benchmarks
46%
18.08.2021
part, darshan-util
, postprocesses the data.
Darshan gathers its data either by compile-time wrappers or dynamic library preloading. For message passing interface (MPI) applications, you can use
46%
10.10.2012
End time is Mon Sep 24 20:25:56 EDT 2012
PS:
Read file for stderr output of this job.
[laytonjb@test1 TEST_OPENLAVA]$ more output.mpi_pi
Enter the number of intervals: (0 quits)
pi is 3
46%
16.01.2013
(nsamples):
12 x = random.random()
13 y = random.random()
14 if (x*x)+(y*y)<1:
15 inside += 1
16
17 mypi = (4.0 * inside)/nsamples
18 pi = comm.reduce(mypi, op=MPI.SUM, root=0)
19
20 if rank