I am running the test program on Darwin 8.11.1, 1.83 Ghz Intel dual
core. My Open MPI install is 1.2.4.
I can't see any allocated shared memory segment on my system (ipcs -
m), although the receiver opens a couple of TCP sockets in listening
mode. It looks like my implementation does not use shared memory. Is
this a configuration issue?
a.out 5628 albertogiannetti 3u unix R,W,NB
0x380b198 0t0 ->0x41ced48
a.out 5628 albertogiannetti 4u unix R,W
0x41ced48 0t0 ->0x380b198
a.out 5628 albertogiannetti 5u IPv4 R,W,NB
0x3d4d920 0t0 TCP *:50969 (LISTEN)
a.out 5628 albertogiannetti 6u IPv4 R,W,NB
0x3e62394 0t0 TCP 192.168.0.10:50970->192.168.0.10:50962
(ESTABLISHED)
a.out 5628 albertogiannetti 7u IPv4 R,W,NB
0x422d228 0t0 TCP *:50973 (LISTEN)
a.out 5628 albertogiannetti 8u IPv4 R,W,NB
0x2dfd394 0t0 TCP 192.168.0.10:50969->192.168.0.10:50975
(ESTABLISHED)
On Apr 23, 2008, at 12:34 PM, Jeff Squyres wrote:
Because on-node communication typically uses shared memory, so we
currently have to poll. Additionally, when using mixed on/off-node
communication, we have to alternate between polling shared memory and
polling the network.
Additionally, we actively poll because it's the best way to lower
latency. MPI implementations are almost always first judged on their
latency, not [usually] their CPU utilization. Going to sleep in a
blocking system call will definitely negatively impact latency.
We have plans for implementing the "spin for a while and then block"
technique (as has been used in other MPI's and middleware layers), but
it hasn't been a high priority.
On Apr 23, 2008, at 12:19 PM, Alberto Giannetti wrote:
Thanks Torje. I wonder what is the benefit of looping on the incoming
message-queue socket rather than using system I/O signals, like read
() or select().
On Apr 23, 2008, at 12:10 PM, Torje Henriksen wrote:
Hi Alberto,
The blocked processes are in fact spin-waiting. While they don't
have
anything better to do (waiting for that message), they will check
their incoming message-queues in a loop.
So the MPI_Recv()-operation is blocking, but it doesn't mean that
the
processes are blocked by the OS scheduler.
I hope that made some sense :)
Best regards,
Torje
On Apr 23, 2008, at 5:34 PM, Alberto Giannetti wrote:
I have simple MPI program that sends data to processor rank 0. The
communication works well but when I run the program on more than 2
processors (-np 4) the extra receivers waiting for data run on >
90%
CPU load. I understand MPI_Recv() is a blocking operation, but why
does it consume so much CPU compared to a regular system read()?
#include <sys/types.h>
#include <unistd.h>
#include <stdio.h>
#include <stdlib.h>
#include <mpi.h>
void process_sender(int);
void process_receiver(int);
int main(int argc, char* argv[])
{
int rank;
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
printf("Processor %d (%d) initialized\n", rank, getpid());
if( rank == 1 )
process_sender(rank);
else
process_receiver(rank);
MPI_Finalize();
}
void process_sender(int rank)
{
int i, j, size;
float data[100];
MPI_Status status;
printf("Processor %d initializing data...\n", rank);
for( i = 0; i < 100; ++i )
data[i] = i;
MPI_Comm_size(MPI_COMM_WORLD, &size);
printf("Processor %d sending data...\n", rank);
MPI_Send(data, 100, MPI_FLOAT, 0, 55, MPI_COMM_WORLD);
printf("Processor %d sent data\n", rank);
}
void process_receiver(int rank)
{
int count;
float value[200];
MPI_Status status;
printf("Processor %d waiting for data...\n", rank);
MPI_Recv(value, 200, MPI_FLOAT, MPI_ANY_SOURCE, 55,
MPI_COMM_WORLD, &status);
printf("Processor %d Got data from processor %d\n", rank,
status.MPI_SOURCE);
MPI_Get_count(&status, MPI_FLOAT, &count);
printf("Processor %d, Got %d elements\n", rank, count);
}
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--
Jeff Squyres
Cisco Systems
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