Thanks for the reply Reuti,
There are two machines: Node1 with 12 physical cores (dual 6 core Xeon) and
Node2 with 4 physical cores (i5-2400).
Regarding scaling on the single 12 core node, not it is also not linear. In
fact it is downright strange. I do not remember the numbers right now but
10 jobs are faster than 11 and 12 are the fastest with peak performance of
approximately 66 Msu/s which is also far from triple the 4 core
performance. This odd non-linear behaviour also happens at the lower job
counts on that 12 core node. I understand the decrease in scaling with
increase in core count on the single node as the memory bandwidth is an
On the 4 core machine the scaling is progressive, ie. every additional job
brings an increase in performance. Single core delivers 8.1 Msu/s while 4
cores deliver 30.8 Msu/s. This is almost linear.
Since my original email I have also installed Open-MX and recompiled
OpenMPI to use it. This has resulted in approximately 10% better
performance using the existing GbE hardware.
On 29 January 2014 19:40, Reuti <reuti_at_[hidden]> wrote:
> Am 29.01.2014 um 03:00 schrieb Victor:
> > I am running a CFD simulation benchmark cavity3d available within
> > It is a parallel friendly Lattice Botlzmann solver library.
> > Palabos provides benchmark results for the cavity3d on several different
> platforms and variables here:
> > The problem that I have is that the benchmark performance on my cluster
> does not scale even close to a linear scale.
> > My cluster configuration:
> > Node1: Dual Xeon 5560 48 Gb RAM
> > Node2: i5-2400 24 Gb RAM
> > Gigabit ethernet connection on eth0
> > OpenMPI 1.6.5 on Ubuntu 12.04.3
> > Hostfile:
> > Node1 -slots=4 -max-slots=4
> > Node2 -slots=4 -max-slots=4
> > MPI command: mpirun --mca btl_tcp_if_include eth0 --hostfile
> /home/mpiuser/.mpi_hostfile -np 8 ./cavity3d 400
> > Problem:
> > cavity3d 400
> > When I run mpirun -np 4 on Node1 I get 35.7615 Mega site updates per
> > When I run mpirun -np 4 on Node2 I get 30.7972 Mega site updates per
> > When I run mpirun --mca btl_tcp_if_include eth0 --hostfile
> /home/mpiuser/.mpi_hostfile -np 8 ./cavity3d 400 I get 47.3538 Mega site
> updates per second
> > I understand that there are latencies with GbE and that there is MPI
> overhead, but this performance scaling still seems very poor. Are my
> expectations of scaling naive, or is there actually something wrong and
> fixable that will improve the scaling? Optimistically I would like each
> node to add to the cluster performance, not slow it down.
> > Things get even worse if I run asymmetric number of mpi jobs in each
> node. For instance running -np 12 on Node1
> Isn't this overloading the machine with only 8 real cores in total?
> > is significantly faster than running -np 16 across Node1 and Node2, thus
> adding Node2 actually slows down the performance.
> The i5-2400 has only 4 cores and no threads.
> It depends on the algorithm how much data has to be exchanged between the
> processes, and this can indeed be worse when used across a network.
> Also: is the algorithm scaling linear when used on node1 only with 8
> cores? When it's "35.7615 " with 4 cores, what result do you get with 8
> cores on this machine.
> -- Reuti
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