42%
12.08.2015
in the name of better performance. Meanwhile, applications and tools have evolved to take advantage of the extra hardware, with applications using OpenMP to utilize the hardware on a single node or MPI to take
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
43%
08.08.2014
-- perhaps 12 to 20 nodes. However, it was just a ``sample'' problem. The complete problem would have started with 128 nodes and quickly moved to several thousand nodes. Although these are not MPI or closely
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
43%
15.01.2014
(MPI), provisioning, and monitoring can also limit the data received and frequency at which it is gathered. As previously mentioned, oversubscribed networks are another source of bottlenecks, so you need
57%
10.09.2013
communication. Next, OpenMP is not always the better choice. In some cases (BT, FT, and SP), the difference was notable. In other cases, the differences was less than 20% (CG, LU, and MG) and even favored MPI (CG
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
50%
17.07.2013
Hadoop version 2 expands Hadoop beyond MapReduce and opens the door to MPI applications operating on large parallel data stores.
... non-MapReduce algorithms has long been a goal of the Hadoop developers. Indeed, YARN now offers new processing frameworks, including MPI, as part of the Hadoop infrastructure.
Please note that existing ...
Hadoop version 2 expands Hadoop beyond MapReduce and opens the door to MPI applications operating on large parallel data stores.
51%
03.07.2013
or processes are used, performance does not improve (wall clock time does not change).
To better understand how Amdahl’s Law works, consider a theoretical application that is 80% parallelizable (20% serial
45%
05.06.2013
to the question of how to get started writing programs for HPC clusters is, “learn MPI programming.” MPI (Message Passing Interface) is the mechanism used to pass data between nodes (really, processes).
Typically