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<p dir="ltr">Hi, </p>
<p dir="ltr">I understand that as mentioned in the faq, due to the
limitations in memory, the scaling is not linear. So, I am trying
to write a proposal to use a supercomputer.<br>
</p>
<p dir="ltr">Its specs are:<br>
</p>
<p dir="ltr">Compute nodes: 82,944 nodes (SPARC64 VIIIfx; 16GB of
memory per node)</p>
<p dir="ltr">8 cores / processor<br>
</p>
<p dir="ltr">Interconnect: Tofu (6-dimensional mesh/torus)
Interconnect<br>
</p>
<p dir="ltr">Each cabinet contains 96 computing nodes,<br>
</p>
<p dir="ltr">One of the requirement is to give the performance of my
current code with my current set of data, and there is a formula
to calculate the estimated parallel efficiency when using the new
large set of data<br>
</p>
<p dir="ltr">There are 2 ways to give performance:<br>
1. Strong scaling, which is defined as how the elapsed time varies
with the number of processors for a fixed<br>
problem. <br>
2. Weak scaling, which is defined as how the elapsed time varies
with the number of processors for a<br>
fixed problem size per processor.<br>
</p>
<p dir="ltr">I ran my cases with 48 and 96 cores with my current
cluster, giving 140 and 90 mins respectively. This is classified
as strong scaling.<br>
</p>
<p dir="ltr">Cluster specs:<br>
</p>
<p dir="ltr">CPU: AMD 6234 2.4GHz<br>
</p>
<p dir="ltr">8 cores / processor (CPU)<br>
</p>
<p dir="ltr">6 CPU / node<br>
</p>
<p dir="ltr">So 48 Cores / CPU<br>
</p>
<p dir="ltr">Not sure abt the memory / node<br>
</p>
<p dir="ltr"><br>
</p>
<p dir="ltr">The parallel efficiency ‘En’ for a given degree of
parallelism ‘n’ indicates how much the program is<br>
efficiently accelerated by parallel processing. ‘En’ is given by
the following formulae. Although their<br>
derivation processes are different depending on strong and weak
scaling, derived formulae are the<br>
same.<br>
</p>
<p dir="ltr">From the estimated time, my parallel efficiency using
Amdahl's law on the current old cluster was 52.7%.<br>
</p>
<p dir="ltr">So is my results acceptable?<br>
</p>
<p dir="ltr">For the large data set, if using 2205 nodes
(2205X8cores), my expected parallel efficiency is only 0.5%. The
proposal recommends value of > 50%.<br>
</p>
<p dir="ltr">Is it possible for this type of scaling in PETSc
(>50%), when using 17640 (2205X8) cores?<br>
</p>
<p dir="ltr">Btw, I do not have access to the system.<br>
</p>
<p dir="ltr"><br>
</p>
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