Hi,
I have a question regarding the performance of parallel I/O vs MPI
communication based calls. I have data which needs to be accessed by
different processors. If the data is in memory then MPI calls (Send/Recv)
does the job. In an another scenario the data is written to a H5 file and
different processors access the respective data using parallel I/O. Would
MPI calls be faster than HDF5 parallel I/O? (data access could be
unstructured)
Regards
Suman Vajjala
Hmm. If I understand the question, I really cannot imagine a scenario where parallel I/O would be "faster" than MPI send/recv calls.
However, there may be a practicality issue here. It may be the case that the data processor k needs is on processor j but processor k doesn't know that processor j has it and processor j doesn't know that processor k needs it. So, there has to be some communication to for the processors to learn that.
And, if those processors are 'somewhere else' in their execution, then you have a significant issue in programming to take advantage of the fact that you could use MPI send/recv to move the data anyways. In the end, it just might be more practical to just read data from the file, even if it is quite a bit slower.
I am not sure I answered the question you asked though 
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov<mailto:miller86@llnl.gov> urgent: markcmiller86@gmail.com
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511
From: Suman Vajjala <suman.geek@gmail.com<mailto:suman.geek@gmail.com>>
Reply-To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>
Date: Monday, April 8, 2013 9:38 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>
Subject: [Hdf-forum] Performance query
Hi,
I have a question regarding the performance of parallel I/O vs MPI communication based calls. I have data which needs to be accessed by different processors. If the data is in memory then MPI calls (Send/Recv) does the job. In an another scenario the data is written to a H5 file and different processors access the respective data using parallel I/O. Would MPI calls be faster than HDF5 parallel I/O? (data access could be unstructured)
Regards
Suman Vajjala
Hi Mark,
Thank you for answering my question. You are right about the
practicality issue. This isn't a serious issue if the data is stored in a
distributed sense with some indicators specifying which processor has the
data. This data is treated as a background database and it doesn't move
during the transfer process.
The reason I asked this question is that I've seen HDF5 taking quite
sometime to read data in an unstructured manner while the MPI calls just
zip through. On an another note, are there any guidelines for parallel I/O
in case of unstructured data?
Regards
Suman
On Tue, Apr 9, 2013 at 10:39 AM, Miller, Mark C. <miller86@llnl.gov> wrote:
Hmm. If I understand the question, I really cannot imagine a scenario
where parallel I/O would be "faster" than MPI send/recv calls.However, there may be a practicality issue here. It may be the case that
the data processor k needs is on processor j but processor k doesn't know
that processor j has it and processor j doesn't know that processor k needs
it. So, there has to be some communication to for the processors to learn
that.And, if those processors are 'somewhere else' in their execution, then
you have a significant issue in programming to take advantage of the fact
that you could use MPI send/recv to move the data anyways. In the end, it
just might be more practical to just read data from the file, even if it is
quite a bit slower.I am not sure I answered the question you asked though
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov urgent: markcmiller86@gmail.com
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511From: Suman Vajjala <suman.geek@gmail.com>
Reply-To: HDF Users Discussion List <hdf-forum@hdfgroup.org>
Date: Monday, April 8, 2013 9:38 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org>
Subject: [Hdf-forum] Performance queryHi,
I have a question regarding the performance of parallel I/O vs MPI
communication based calls. I have data which needs to be accessed by
different processors. If the data is in memory then MPI calls (Send/Recv)
does the job. In an another scenario the data is written to a H5 file and
different processors access the respective data using parallel I/O. Would
MPI calls be faster than HDF5 parallel I/O? (data access could be
unstructured)Regards
Suman Vajjala_______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@hdfgroup.org
http://mail.hdfgroup.org/mailman/listinfo/hdf-forum_hdfgroup.org
Hi Suman,
I think you are hinting at the fact that unstructured data is harder to manage with true concurrent parallel I/O to a single, shared file, right? Yeah, it is.
Honestly, I don't have much experience with that. My impression has always been that the more information you can give HDF5 in the H5Dwrite/H5Dread calls, the better it and the layers below it (MPI-IO, luster/gpfs, etc.) can take advantage of things and 'do the right/best thing'.
So, I guess one piece of advice is to try to characterize the application's I/O needs in requests that are 'as large as possible'. And, if its practical to do so, try to allow processors to 'coordinate' their I/O by issuing collective instead of independent requests. If parts of some large array are being read onto many processors, let each processor define the its piece(s) of that array using HDF5 data selections and then have all of them do a collective H5Dread. In theory, that lets MPI-IO and lustre do whatever 'magic' is possible to aggregate all the data into a few I/O requests to the filesystem but buffer and disperse it to whatever processors need it efficiently. At least that is how I think HDF5/MPI-IO/Luster will operate in theory. There may be a lot of issues to making it efficient in practice.
Good luck.
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov<mailto:miller86@llnl.gov> urgent: markcmiller86@gmail.com
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511
From: Suman Vajjala <suman.geek@gmail.com<mailto:suman.geek@gmail.com>>
Date: Monday, April 8, 2013 10:25 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>, "Miller, Mark C." <miller86@llnl.gov<mailto:miller86@llnl.gov>>
Subject: Re: [Hdf-forum] Performance query
Hi Mark,
Thank you for answering my question. You are right about the practicality issue. This isn't a serious issue if the data is stored in a distributed sense with some indicators specifying which processor has the data. This data is treated as a background database and it doesn't move during the transfer process.
The reason I asked this question is that I've seen HDF5 taking quite sometime to read data in an unstructured manner while the MPI calls just zip through. On an another note, are there any guidelines for parallel I/O in case of unstructured data?
Regards
Suman
On Tue, Apr 9, 2013 at 10:39 AM, Miller, Mark C. <miller86@llnl.gov<mailto:miller86@llnl.gov>> wrote:
Hmm. If I understand the question, I really cannot imagine a scenario where parallel I/O would be "faster" than MPI send/recv calls.
However, there may be a practicality issue here. It may be the case that the data processor k needs is on processor j but processor k doesn't know that processor j has it and processor j doesn't know that processor k needs it. So, there has to be some communication to for the processors to learn that.
And, if those processors are 'somewhere else' in their execution, then you have a significant issue in programming to take advantage of the fact that you could use MPI send/recv to move the data anyways. In the end, it just might be more practical to just read data from the file, even if it is quite a bit slower.
I am not sure I answered the question you asked though
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov<mailto:miller86@llnl.gov> urgent: markcmiller86@gmail.com<mailto:markcmiller86@gmail.com>
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511
From: Suman Vajjala <suman.geek@gmail.com<mailto:suman.geek@gmail.com>>
Reply-To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>
Date: Monday, April 8, 2013 9:38 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>
Subject: [Hdf-forum] Performance query
Hi,
I have a question regarding the performance of parallel I/O vs MPI communication based calls. I have data which needs to be accessed by different processors. If the data is in memory then MPI calls (Send/Recv) does the job. In an another scenario the data is written to a H5 file and different processors access the respective data using parallel I/O. Would MPI calls be faster than HDF5 parallel I/O? (data access could be unstructured)
Regards
Suman Vajjala
_______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@hdfgroup.org<mailto:Hdf-forum@hdfgroup.org>
http://mail.hdfgroup.org/mailman/listinfo/hdf-forum_hdfgroup.org
Thanks a lot Mark. Collective communication may not always be possible as
two processors may access to the same data. Are you suggesting that one
needs to separate I/O requests into collective and independent modes? Can
one do a collective I/O even when the data is non-contiguous?
Regards
Suman
On Tue, Apr 9, 2013 at 11:06 AM, Miller, Mark C. <miller86@llnl.gov> wrote:
Hi Suman,
I think you are hinting at the fact that unstructured data is harder to
manage with true concurrent parallel I/O to a single, shared file, right?
Yeah, it is.Honestly, I don't have much experience with that. My impression has
always been that the more information you can give HDF5 in the
H5Dwrite/H5Dread calls, the better it and the layers below it (MPI-IO,
luster/gpfs, etc.) can take advantage of things and 'do the right/best
thing'.So, I guess one piece of advice is to try to characterize the
application's I/O needs in requests that are 'as large as possible'. And,
if its practical to do so, try to allow processors to 'coordinate' their
I/O by issuing collective instead of independent requests. If parts of some
large array are being read onto many processors, let each processor define
the its piece(s) of that array using HDF5 data selections and then have all
of them do a collective H5Dread. In theory, that lets MPI-IO and lustre do
whatever 'magic' is possible to aggregate all the data into a few I/O
requests to the filesystem but buffer and disperse it to whatever
processors need it efficiently. At least that is how I think
HDF5/MPI-IO/Luster will operate in theory. There may be a lot of issues to
making it efficient in practice.Good luck.
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov urgent: markcmiller86@gmail.com
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511From: Suman Vajjala <suman.geek@gmail.com>
Date: Monday, April 8, 2013 10:25 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org>, "Miller, Mark C."
<miller86@llnl.gov>
Subject: Re: [Hdf-forum] Performance queryHi Mark,
Thank you for answering my question. You are right about the
practicality issue. This isn't a serious issue if the data is stored in a
distributed sense with some indicators specifying which processor has the
data. This data is treated as a background database and it doesn't move
during the transfer process.The reason I asked this question is that I've seen HDF5 taking quite
sometime to read data in an unstructured manner while the MPI calls just
zip through. On an another note, are there any guidelines for parallel I/O
in case of unstructured data?Regards
SumanOn Tue, Apr 9, 2013 at 10:39 AM, Miller, Mark C. <miller86@llnl.gov>wrote:
Hmm. If I understand the question, I really cannot imagine a scenario
where parallel I/O would be "faster" than MPI send/recv calls.However, there may be a practicality issue here. It may be the case
that the data processor k needs is on processor j but processor k doesn't
know that processor j has it and processor j doesn't know that processor k
needs it. So, there has to be some communication to for the processors to
learn that.And, if those processors are 'somewhere else' in their execution, then
you have a significant issue in programming to take advantage of the fact
that you could use MPI send/recv to move the data anyways. In the end, it
just might be more practical to just read data from the file, even if it is
quite a bit slower.I am not sure I answered the question you asked though
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov urgent: markcmiller86@gmail.com
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511From: Suman Vajjala <suman.geek@gmail.com>
Reply-To: HDF Users Discussion List <hdf-forum@hdfgroup.org>
Date: Monday, April 8, 2013 9:38 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org>
Subject: [Hdf-forum] Performance queryHi,
I have a question regarding the performance of parallel I/O vs MPI
communication based calls. I have data which needs to be accessed by
different processors. If the data is in memory then MPI calls (Send/Recv)
does the job. In an another scenario the data is written to a H5 file and
different processors access the respective data using parallel I/O. Would
MPI calls be faster than HDF5 parallel I/O? (data access could be
unstructured)Regards
Suman Vajjala_______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@hdfgroup.org
http://mail.hdfgroup.org/mailman/listinfo/hdf-forum_hdfgroup.org
Thanks a lot Mark. Collective communication may not always be possible as two processors may access to the same data. Are you suggesting that one needs to separate I/O requests into collective and independent modes?
Yes, I guess I am. I mean, if its practical to do so.
Can one do a collective I/O even when the data is non-contiguous?
You mean non-contiguous in the file? Yes, you can do collective I/O even if the data is not contiguous in the file. That’s what data selections are good at. But every processor (in the communicator used to open the file) must participate in a collective operation.
Regards
Suman
On Tue, Apr 9, 2013 at 11:06 AM, Miller, Mark C. <miller86@llnl.gov<mailto:miller86@llnl.gov>> wrote:
Hi Suman,
I think you are hinting at the fact that unstructured data is harder to manage with true concurrent parallel I/O to a single, shared file, right? Yeah, it is.
Honestly, I don't have much experience with that. My impression has always been that the more information you can give HDF5 in the H5Dwrite/H5Dread calls, the better it and the layers below it (MPI-IO, luster/gpfs, etc.) can take advantage of things and 'do the right/best thing'.
So, I guess one piece of advice is to try to characterize the application's I/O needs in requests that are 'as large as possible'. And, if its practical to do so, try to allow processors to 'coordinate' their I/O by issuing collective instead of independent requests. If parts of some large array are being read onto many processors, let each processor define the its piece(s) of that array using HDF5 data selections and then have all of them do a collective H5Dread. In theory, that lets MPI-IO and lustre do whatever 'magic' is possible to aggregate all the data into a few I/O requests to the filesystem but buffer and disperse it to whatever processors need it efficiently. At least that is how I think HDF5/MPI-IO/Luster will operate in theory. There may be a lot of issues to making it efficient in practice.
Good luck.
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov<mailto:miller86@llnl.gov> urgent: markcmiller86@gmail.com<mailto:markcmiller86@gmail.com>
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511
From: Suman Vajjala <suman.geek@gmail.com<mailto:suman.geek@gmail.com>>
Date: Monday, April 8, 2013 10:25 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>, "Miller, Mark C." <miller86@llnl.gov<mailto:miller86@llnl.gov>>
Subject: Re: [Hdf-forum] Performance query
Hi Mark,
Thank you for answering my question. You are right about the practicality issue. This isn't a serious issue if the data is stored in a distributed sense with some indicators specifying which processor has the data. This data is treated as a background database and it doesn't move during the transfer process.
The reason I asked this question is that I've seen HDF5 taking quite sometime to read data in an unstructured manner while the MPI calls just zip through. On an another note, are there any guidelines for parallel I/O in case of unstructured data?
Regards
Suman
On Tue, Apr 9, 2013 at 10:39 AM, Miller, Mark C. <miller86@llnl.gov<mailto:miller86@llnl.gov>> wrote:
Hmm. If I understand the question, I really cannot imagine a scenario where parallel I/O would be "faster" than MPI send/recv calls.
However, there may be a practicality issue here. It may be the case that the data processor k needs is on processor j but processor k doesn't know that processor j has it and processor j doesn't know that processor k needs it. So, there has to be some communication to for the processors to learn that.
And, if those processors are 'somewhere else' in their execution, then you have a significant issue in programming to take advantage of the fact that you could use MPI send/recv to move the data anyways. In the end, it just might be more practical to just read data from the file, even if it is quite a bit slower.
I am not sure I answered the question you asked though
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov<mailto:miller86@llnl.gov> urgent: markcmiller86@gmail.com<mailto:markcmiller86@gmail.com>
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511
From: Suman Vajjala <suman.geek@gmail.com<mailto:suman.geek@gmail.com>>
Reply-To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>
Date: Monday, April 8, 2013 9:38 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org<mailto:hdf-forum@hdfgroup.org>>
Subject: [Hdf-forum] Performance query
Hi,
I have a question regarding the performance of parallel I/O vs MPI communication based calls. I have data which needs to be accessed by different processors. If the data is in memory then MPI calls (Send/Recv) does the job. In an another scenario the data is written to a H5 file and different processors access the respective data using parallel I/O. Would MPI calls be faster than HDF5 parallel I/O? (data access could be unstructured)
Regards
Suman Vajjala
_______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@hdfgroup.org<mailto:Hdf-forum@hdfgroup.org>
http://mail.hdfgroup.org/mailman/listinfo/hdf-forum_hdfgroup.org
Thanks once again for the advice.
Regards
Suman
On Tue, Apr 9, 2013 at 11:23 AM, Miller, Mark C. <miller86@llnl.gov> wrote:
Thanks a lot Mark. Collective communication may not always be possible
as two processors may access to the same data. Are you suggesting that one
needs to separate I/O requests into collective and independent modes?Yes, I guess I am. I mean, if its practical to do so.
Can one do a collective I/O even when the data is non-contiguous?
You mean non-contiguous in the file? Yes, you can do collective I/O even
if the data is not contiguous in the file. That’s what data selections are
good at. But every processor (in the communicator used to open the file)
must participate in a collective operation.Regards
SumanOn Tue, Apr 9, 2013 at 11:06 AM, Miller, Mark C. <miller86@llnl.gov>wrote:
Hi Suman,
I think you are hinting at the fact that unstructured data is harder to
manage with true concurrent parallel I/O to a single, shared file, right?
Yeah, it is.Honestly, I don't have much experience with that. My impression has
always been that the more information you can give HDF5 in the
H5Dwrite/H5Dread calls, the better it and the layers below it (MPI-IO,
luster/gpfs, etc.) can take advantage of things and 'do the right/best
thing'.So, I guess one piece of advice is to try to characterize the
application's I/O needs in requests that are 'as large as possible'. And,
if its practical to do so, try to allow processors to 'coordinate' their
I/O by issuing collective instead of independent requests. If parts of some
large array are being read onto many processors, let each processor define
the its piece(s) of that array using HDF5 data selections and then have all
of them do a collective H5Dread. In theory, that lets MPI-IO and lustre do
whatever 'magic' is possible to aggregate all the data into a few I/O
requests to the filesystem but buffer and disperse it to whatever
processors need it efficiently. At least that is how I think
HDF5/MPI-IO/Luster will operate in theory. There may be a lot of issues to
making it efficient in practice.Good luck.
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov urgent: markcmiller86@gmail.com
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511From: Suman Vajjala <suman.geek@gmail.com>
Date: Monday, April 8, 2013 10:25 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org>, "Miller, Mark
C." <miller86@llnl.gov>
Subject: Re: [Hdf-forum] Performance queryHi Mark,
Thank you for answering my question. You are right about the
practicality issue. This isn't a serious issue if the data is stored in a
distributed sense with some indicators specifying which processor has the
data. This data is treated as a background database and it doesn't move
during the transfer process.The reason I asked this question is that I've seen HDF5 taking
quite sometime to read data in an unstructured manner while the MPI calls
just zip through. On an another note, are there any guidelines for parallel
I/O in case of unstructured data?Regards
SumanOn Tue, Apr 9, 2013 at 10:39 AM, Miller, Mark C. <miller86@llnl.gov>wrote:
Hmm. If I understand the question, I really cannot imagine a scenario
where parallel I/O would be "faster" than MPI send/recv calls.However, there may be a practicality issue here. It may be the case
that the data processor k needs is on processor j but processor k doesn't
know that processor j has it and processor j doesn't know that processor k
needs it. So, there has to be some communication to for the processors to
learn that.And, if those processors are 'somewhere else' in their execution, then
you have a significant issue in programming to take advantage of the fact
that you could use MPI send/recv to move the data anyways. In the end, it
just might be more practical to just read data from the file, even if it is
quite a bit slower.I am not sure I answered the question you asked though
Mark
--
Mark C. Miller, Lawrence Livermore National Laboratory
================!!LLNL BUSINESS ONLY!!================
miller86@llnl.gov urgent: markcmiller86@gmail.com
T:8-6 (925)-423-5901 M/W/Th:7-12,2-7 (530)-753-8511From: Suman Vajjala <suman.geek@gmail.com>
Reply-To: HDF Users Discussion List <hdf-forum@hdfgroup.org>
Date: Monday, April 8, 2013 9:38 PM
To: HDF Users Discussion List <hdf-forum@hdfgroup.org>
Subject: [Hdf-forum] Performance queryHi,
I have a question regarding the performance of parallel I/O vs MPI
communication based calls. I have data which needs to be accessed by
different processors. If the data is in memory then MPI calls (Send/Recv)
does the job. In an another scenario the data is written to a H5 file and
different processors access the respective data using parallel I/O. Would
MPI calls be faster than HDF5 parallel I/O? (data access could be
unstructured)Regards
Suman Vajjala_______________________________________________
Hdf-forum is for HDF software users discussion.
Hdf-forum@hdfgroup.org
http://mail.hdfgroup.org/mailman/listinfo/hdf-forum_hdfgroup.org
