[MXNET-366]Extend MXNet Distributed Training by AllReduce #10696

threeleafzerg · 2018-04-26T05:36:31Z

Description

We extend MXNet distributed training by adding one new type of kvstore (dist_sync_allreduce).
In this type of kvstore, since there's no parameter server, we replace original kvstore apis push and pull with one single api pushpull. We also add one api broadcast to broadcast the weight in root rank to other nodes. You can refer API Spec part in the design doc for details. We created a new thread on each node to sync and do allreduce through mpi.
Currently, we implement the CPU part and leave the place holder to GPU. It's easy to extend to GPU part with mpi support or nccl v2 support.

Following is the design doc
https://docs.google.com/document/d/1e4anwDiS18cWP49FAghU6tqqdtnRKUcbNJJxvhIfvIA/edit#heading=h.t762l56r1094

Performance and Accuracy

For Performance, our testing environment: Machine: SKX6148, Network: 10GbE, Topology: VGG16, Local Batch Size: 64 Single Node FPS: 27.3 (pic/second)

For Accuracy, we compared top-1 and top-5 accuracy curve between 4 P100 GPU (with original kvstore dist_device) and 4 SKX6148 CPU (with new kvstore dist_sync_allreduce). We found the accuracy curve is highly matched. (GPU: 130 epochs. CPU: 113 epochs.)

threeleafzerg · 2018-04-26T07:15:15Z

For PS-Lite, I change to the ps-lite branch to my private fork. Because when enabling dist_sync_mpi kvstore, we depends upon ps-lite google protobuf to do formatted message communication. But original google protobuf in ps-lite (v2.5.1) has bug on message serialization and de-serialization. So I change the google protobuf in ps-lite (v3.5.1).

threeleafzerg · 2018-04-26T07:21:40Z

@pengzhao-intel

chinakook · 2018-04-26T07:58:04Z

The future of traning NN is belong to CPU.

piiswrong · 2018-04-26T17:41:03Z

@mli

pengzhao-intel · 2018-05-03T12:40:59Z

@mli @rahul003
Could you help take the review for this PR?

rahul003 · 2018-05-03T19:21:46Z

@threeleafzerg Could you share instructions for building this, and add this as a step to the CI to verify the build. It looks like I need to install MPI separately? Or can we include it in the src as a 3rd party lib?

rahul003 · 2018-05-03T19:25:43Z

About the numbers above 'Local Batch Size: 64' refers to 64 across many GPUs? Can you run a benchmark with higher batch size like [512 with 8 gpus or 256 with 4 gpus, for resnet50 imagenet] and compare the scalability?

rahul003 · 2018-05-03T21:48:25Z

I installed MPI with sudo apt-get install mpich on ubuntu and gave MPIROOT as /usr/local/bin/mpi . Build failed saying mpi.h not found. Am I doing something wrong?

threeleafzerg · 2018-05-04T01:32:20Z

@rahul003
The build instruction is as follows:
USE_DIST_KVSTORE = 1
USE_ALLREDUCE_DIST_KVSTORE = 1
MPI_ROOT=/usr/lib/openmpi
We let the end user to select which mpi to use. (openmpi, mpich, or intel mpi.) That's why we don't include src as 3rd party lib. You can check horovod, they play the same trick. https://github.com/uber/horovod#install
So the end user need to install MPI separately.
Can you try latest open mpi? We tried both open mpi and intel mpi, their release dir structure looks like following:
/home/zhouhaiy/openmpi/build
[zhouhaiy@mlt-ace build]$ ls
bin etc include lib share
Looks like mpich release dir is not same as open mpi, I will have a check.

Certainly, we can also do the following logic:
If env MPI_ROOT is set, we use this mpi lib version from this env, otherwise we download open source 3rd party mpi source code, compile build and mxnet depends upon it.

Which one do you prefer? Need consensus.

threeleafzerg · 2018-05-04T01:54:06Z

@rahul003 Local Batch Size: 64 means every node's batch size is 64 so global batch size is 64 * 8 = 512.
Currently, the result is based upon CPU. For resnet50, we tried, the scaling efficiency close to 99%. Our currently implementation covers CPU and leaves place holder for GPU.

threeleafzerg · 2018-05-04T03:28:47Z

@rahul003 For mpich, if you directly install ubuntu package of mpich, it's header file and lib file is not in the same sub folder. I suggest to download mpich (compile and build). (https://www.mpich.org/downloads/)
The built mpich has the same release dir as open mpi and intel mpi.
[zhouhaiy@mlt-ace build]$ pwd
/home/zhouhaiy/mpich2/build
[zhouhaiy@mlt-ace build]$ ls
bin include lib share
I already tried it and mxnet can build with mpich2.

rahul003 · 2018-05-04T06:06:35Z

Implementation only for CPU is very restrictive. Are you also trying to implement for GPU? Are you running into any issues? Scaling efficiency is something we need a lot of work on, as my runs with large number of machines are showing. It would be awesome if we can have MPI for GPU as well. I'm happy to offer any help needed to get this done.
You mentioned efficiency for resnet50, but for what batch size? Are all these training numbers on CPU?
Leaving the flexibility of which MPI to user is good for advanced users. But for lot of people it adds unnecessary complexity IMO. How do the different MPI frameworks differ? Is one framework more performant in your experience? Should we choose that as default and provide a way for user to replace that with their own framework using the environment variable or make flag. I would really recommend this option.
@reminisce This PR tries to change protobuf to proto3. I wanted to draw your attention to that change. Could you review that in light of your plan to move to proto3 for mxboard, etc.

Also ccing @eric-haibin-lin for reviews

rahul003 · 2018-05-04T05:49:59Z

src/mpi_collectives/src/mpi_collectives.cxx

@@ -0,0 +1,827 @@
+/*


MXNet has no file as cxx. Could you change to cc?

cxx is selected on purpose to solve compilation dependency originally.
Our mpi_collectives.cxx depends upon generated mpi_message.pb.cc and mpi_message.pb.h to compile.
makefile rule SRC = $(wildcard src////.cc src///.cc src//.cc src/.cc) will contain mpi_collectives.cc if we don't change the suffix. $SRC has its own compilation rule. mpi related files has another compilation rule. That's why I use different suffix.

But I know your concern, I can use makefile built-in function filterout to remove mpi files in SRC. I will change its suffix to cc.

rahul003 · 2018-05-04T05:51:26Z

src/mpi_collectives/include/mpi_util.h

+
+#if DEBUG_ON
+    #define MXMPI_DEBUG(rank, fmt, args...)  \
+        do {    \


Curious, why this do{}while(0) syntax?

Agree with you. Not necessary. I will remove it.

threeleafzerg · 2018-05-04T08:45:36Z

@rahul003
For GPU, I agree with your comment. But the majority code of this PR is the infrastructure of adding allreduce into MXNet which is shared by both CPU and GPU. Currently we leave the place holder for GPU for future extension. We don't run into any issue on GPU and we enable CPU firstly simply because we
currently have a lot CPU multi-node environment We can discuss further about how to add GPU extension. @pengzhao-intel Patric will shed more lights upon it.

For resnet50, local batch size 64, global batch size 64 * 8 = 512. (8 machine) Yes, we trained all on CPU.

In general, all reduce performance should be similar for openmpi and mpich. Intel mpi has better performance on all reduce performance, but it's not free software though it's run-time part is free. I agree you that we select openmpi as default mpi if no one objects. (we will download open mpi zip in 3rd party and compile it.)

For proto3, I tested original kvstore type dist_sync, it works fine for PS-Lite. Moreover, we just use protobuf 3.5.1. For PS-Lite it still uses proto2. (just need to specify its version explicitly.)

threeleafzerg · 2018-05-08T11:59:27Z

@rahul003 Already finished code modification according to your comments. I add mpich as default mpi and I tried it works fine. Let me know if there's any questions.

pengzhao-intel · 2018-05-10T02:32:04Z

@eric-haibin-lin @rahul003 The defined works are done from our side now. Both the functionality and performance are qualified.

Please help take a review again. Feel free to let us know for any open issues.

eric-haibin-lin

Is the current CI blocking you from adding unit tests?

eric-haibin-lin · 2018-05-10T06:24:43Z

.gitmodules

@@ -6,7 +6,7 @@
 	url = https://github.com/dmlc/dmlc-core.git
 [submodule "3rdparty/ps-lite"]
 	path = 3rdparty/ps-lite
-	url = https://github.com/dmlc/ps-lite
+	url = https://github.com/threeleafzerg/ps-lite.git


Please remember to revert after dmlc/ps-lite#137 is merged.

eric-haibin-lin · 2018-05-10T06:26:08Z

Makefile

@@ -339,12 +339,32 @@ ifeq ($(USE_DIST_KVSTORE), 1)
 	LDFLAGS += $(PS_LDFLAGS_A)
 endif

+# for kvstore with type dist_sync_mpi


@szha could you help review Makefile?

eric-haibin-lin · 2018-05-10T06:33:49Z

python/mxnet/kvstore.py

+            raise Exception("This api is not supported for kvstore with type %s. \
+                             Please use pushpull instead."%self.type)
+
+    def pushpull(self, key, ins, outs, priority=0):


Does this api invoke updater at all?

When using dist_sync_mpi kvstore, its gradient updater policy is the same as kvstore local. It always use updater, you can check api set_optimizer in kvstore in this patch. Hope I didn't misunderstand your meaning.

I guess the answer to Haibin's question is that update_on_kvstore is set to False when using this MPI kvstore.

threeleafzerg · 2018-05-10T08:06:50Z

@eric-haibin-lin Currently, in nightly test-all.sh, dist_sync_kvstore.py is added but it's under MXNet GPU build. We will add dist_sync_mpi_kvstore.py there and run it in CI. In nightly, this test script will be enabled until GPU is supported.

szha · 2018-05-10T17:50:03Z

Makefile

@@ -382,6 +402,10 @@ else
 	endif
 endif

+MPI_SRC = $(wildcard  src/mpi_collectives/src/*.cc)


SRC_FILTER is the same.

@szha I know that. SRC_FILTER is put here for future extension. Because maybe in future, another source code which is put within src/ need different compilation rule same as MPI_SRC. SRC_FILTER will looks like SRC_FILTER += $(wildcard src/[other-component]/src/*.cc)

Let's put the simplest possible code that does the job in the codebase, and let the next person worry about how to use different compilation rules for new files. Most likely if anyone other than you works on this code, your comment here will be no where to be found by the contributor. "Potential extension" is often a synonym for tech debt.

OK. Then how about:
MPI_SRC = $(wildcard src/mpi_collectives/src/*.cc)
...
SRC_FILTER = $(MPI_SRC)

eric-haibin-lin

@ptrendx @DickJC123 any comments on the reserved interface for CUDA MPI/NCCL in this PR?

eric-haibin-lin · 2018-05-11T16:57:14Z

include/mxnet/kvstore.h

+  virtual void PushPull(const std::vector<int> &keys,
+                        const std::vector<NDArray*> &in_values,
+                        const std::vector<NDArray*> &out_values,
+                        int priority = 0) {}


Shall we add LOG(FATAL) to the default implementation?

OK. I will add them

eric-haibin-lin · 2018-05-11T17:01:55Z

python/mxnet/kvstore.py

@@ -166,6 +166,9 @@ def push(self, key, value, priority=0):
        There is no synchronization between workers.
        One can use ``_barrier()`` to sync all workers.

+        Note: This api is not supported for kvstore with type dist_sync_mpi. Use pushpull


nit: we can improve it with

:py:meth:`pushpull`

so that the doc renders with nice hyperlinks. See https://mxnet.incubator.apache.org/versions/master/api/python/gluon/gluon.html#mxnet.gluon.ParameterDict.get_constant for example

eric-haibin-lin · 2018-05-11T17:07:28Z

src/mpi_collectives/include/mpi_collectives.h

+ * Copyright (c) 2018 by Contributors
+ */
+
+#ifndef MXNET_MPI_COLLECTIVES_INCLUDE_MPI_COLLECTIVES_H_


Not sure if we want to create a src/mpi_collectives folder. This is only used by kvstore. Maybe inside the kvstore folder? The namespace is also under mxnet::kvstore.

Haibin, do you mean the folder structure should be like
src/kvstore/mpi_collectives?
Since it's only used for mpi_collectives, it's OK.

eric-haibin-lin · 2018-05-11T17:10:38Z

src/mpi_collectives/include/mpi_collectives.h

+
+namespace mxnet {
+namespace kvstore {
+


Although some relevant documentations are added to c_api.h, I still expect header only files like this come with detailed documentation for functionality description, arguments and return values.

OK. I will add doxgen-style comment for these functions.

eric-haibin-lin · 2018-05-11T17:11:38Z

src/mpi_collectives/include/mpi_util.h

+#include <stdio.h>
+#include <vector>
+
+#define DEBUG_ON 0


MPI_UTIL_DEBUG_ON

OK. I will refine it.

eric-haibin-lin · 2018-05-11T17:22:43Z

src/mpi_collectives/include/mpi_wrapper.h

+
+template<typename DType>
+MPI_Datatype MPI_Data_Type_Cast(void) {
+  LOG(FATAL) << "Need to template specialization to get mpi data type";


Why do you need a default definition that throw errors at runtime? You already added template specialization. Would a template definition like below be sufficient?

template<typename DType> MPI_Datatype MPI_Data_Type_Cast(void);

My original point is that if anyone used unsupported data type it can be caught by run time exception. In your way, it looks like any unsupported data type will be caught in compilation time.
OK for me to remove default implementation.

eric-haibin-lin · 2018-05-11T17:25:25Z

src/mpi_collectives/src/mpi_collectives.cc

+typedef std::unordered_map<std::string, std::vector<MPIRequest> > MessageTable;
+
+struct MPIGlobalState {
+  std::atomic_flag initialized_flag = ATOMIC_FLAG_INIT;


Some descriptions would be helpful

I will add it in next commit.

eric-haibin-lin · 2018-05-11T17:28:05Z

src/kvstore/kvstore_dist_sync_mpi.h

+                int priority) override {
+    int ret = MXMPIAllReduce(keys, in_values, out_values, priority);
+    if (ret != 0) {
+      LOG(WARNING) << "MXMPIAllReduce is not successful. ret: " << ret;


Why is it a LOG(WARNING) instead of LOG(FATAL)?

agree with you.

threeleafzerg · 2018-05-15T13:40:33Z

@eric-haibin-lin
Hi haibin, I have already finished code modification according to your comments. Any question, please let me know. Thanks!
Note: Upon our internal code review (intel), I changed the following naming:
dist_sync_mpi -> dist_sync_allreduce
mpi_collectives -> collectives
MPI_Wrapper -> COLL_Wrapper
Because the collectives can be implemented not only in MPI library. (e.g. nccl library)
The corresponding design doc has already been updated.
https://docs.google.com/document/d/1e4anwDiS18cWP49FAghU6tqqdtnRKUcbNJJxvhIfvIA/edit#heading=h.t762l56r1094
Gluon is also supported.

congxie1108 · 2018-07-03T20:11:10Z

In kvstore_dist_sync_allreduce.h:

Since the allreduce kvstore is now derived from kvstore_local, you don't need to override push/pull. Simply overriding PushImpl/PullImpl/PullRowSparseImpl should work.
It would be better if you could move the definition of "CheckUnique" from kvstoredist to kvstorelocal and reuse it in allreduce. It is unnecessary to copy the same code from kvstoredist.

congxie1108 · 2018-07-03T20:19:28Z

For some custom mpi versions (such as openmpi), directly using gcc/g++ may cause some problem (though it seems ok now for mpich). I strongly recommend to add some rules in the makefile so that when the USE_ALLREDUCE_DIST_KVSTORE flag is on, gcc/g++ will be replaced by mpicc/mpiCC or mpiCXX.

threeleafzerg · 2018-07-04T01:09:11Z

@marcoabreu Finished code modification according to your review comments.

threeleafzerg · 2018-07-04T01:15:30Z

@xcgoner
Thanks for your review comment!

I think it's better to override explicitly in direct interface (push and pull) to warn the end user not to use these interfaces in this allreduce kvstore.
You are right. Finished code modification according to your comments.
what's problem you meet when your use openmpi? It looks like in my local machine, openmpi can be used. But the performance is very bad because I don't know how to configure openmpi.

congxie1108 · 2018-07-05T01:49:26Z

@threeleafzerg
Thanks for the quick response.

Explicit overriding makes sense to me according to your explanation, though overriding 4 functions and repeating the same codes seems a little bit redundant to me. But it's ok anyway.
I was trying to use the latest stable version of openmpi (version 3.1) instead of the default old version in ubuntu. There was some kind of link error, which disappears when I used mpicc/mpiCC to replace gcc/g++. It seems that if you are using the default old version of openmpi in ubuntu (installed by apt-get), gcc/g++ will be ok.

threeleafzerg · 2018-07-05T02:15:27Z

@xcgoner I am using the openmpi(version 3.1) too and I didn't encounter any link error. (My Linux dist. centos 7) I tried to replace default g++ with mpicxx (change $(CXX)), build is OK. But one library cannot be found (libmklml_intel.so) in the runtime. I can co-work with MKLDNN support team with that, but this may not be included in this PR.

BTW: After you use mpicc to build with openmpi successfully, does the mxnet allreduce kvstore works fine?

congxie1108 · 2018-07-05T18:13:58Z

@threeleafzerg
I'm using openmpi because I wanna experimentally try some new feature which is only provided by openmpi. I think for this PR you can leave the compilers to be gcc/g++. I will start my own PR once I get it done.
Openmpi seems fine when I use it. But I have not fully tested the performance or compared it with mpich yet. I will report the follow up once I get it done after your PR is completed.

threeleafzerg · 2018-07-05T23:38:12Z

@xcgoner
OK. If you have any question, don't hesitate to post the question.

2. Change the implementation of allreduce kvstore's barrier

lupesko · 2018-08-06T20:34:03Z

Thanks for the great contribution @threeleafzerg !
@anirudh2290 @eric-haibin-lin - can you guys check this out? (design doc as a reference)

threeleafzerg · 2018-09-07T02:03:26Z

Since mxnet will integrate horovod into the framework, I decided to close this PR.

pengzhao-intel · 2018-09-07T02:28:40Z

Really thank @threeleafzerg's efforts to enable the first version of AllReduce solution with MXNet 🥇
Actually, the current implementation is partially merged into Horovod solution. And the new solution will take the advantages of both this PR and Horovod so it will be very nice for the community 👍

NanYan1119 · 2018-09-10T08:13:28Z

I have a problem when test the allreduce version.

I clone the master code from https://github.com/threeleafzerg/incubator-mxnet.
I use "make -j $(nproc) USE_OPENCV=1 USE_BLAS=openblas USE_CUDA=1 USE_CUDA_PATH=/usr/local/cuda USE_CUDNN=1 USE_PROFILER=1 USE_DIST_KVSTORE=1 USE_ALLREDUCE_DIST_KVSTORE=1 MPI_ROOT=/usr/local/openmpi" to compile.
But when I run the script ~/incubator-mxnet/tests/nightly/dist_allreduce_sync_kvstore.py, it end with an error:

pure virtual method called
terminate called without an active exception
*** Process received signal ***
Signal: Aborted (6)
Signal code: (-6)

It seems the error occurred in destruct the kvstore, can anyone help me? @threeleafzerg

threeleafzerg · 2018-09-13T00:38:51Z

@NanYan1119 I also noticed this bug. I will debug it this weekend.

threeleafzerg · 2018-09-13T01:30:36Z

@NanYan1119 Since horovod will be the official all reduce solution in mxnet, can you switch to mxnet. horovod ? Thanks!

threeleafzerg · 2018-09-13T01:47:04Z

@NanYan1119 For mxnet.horovod details, please consult eric-haibin-lin or ctcyang

NanYan1119 · 2018-09-17T09:09:42Z

@threeleafzerg Sorry for the late reply！It's a goog idea. Do you know when the horovod for mxnet will be released?

threeleafzerg · 2018-09-17T12:08:14Z

@NanYan1119 You can consult with ctcyang. Their proposal has already been posted in design wiki.
https://cwiki.apache.org/confluence/display/MXNET/Horovod-MXNet+Integration

NanYan1119 · 2018-09-17T12:26:42Z

@threeleafzerg Thank you! I will notice that.

threeleafzerg requested a review from szha as a code owner April 26, 2018 05:36

threeleafzerg changed the title ~~Extend MXNet Distributed Training by MPI AllReduce~~ [MXNET-366]Extend MXNet Distributed Training by MPI AllReduce Apr 28, 2018

threeleafzerg mentioned this pull request May 2, 2018

Change google protobuf from v2.5.0 to v3.5.1 in ps-lite dmlc/ps-lite#137

Merged

threeleafzerg force-pushed the master branch from b692a77 to 5cbc7de Compare May 2, 2018 08:40

rahul003 reviewed May 4, 2018

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eric-haibin-lin self-assigned this May 10, 2018

eric-haibin-lin reviewed May 10, 2018

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szha reviewed May 10, 2018

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eric-haibin-lin reviewed May 11, 2018

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threeleafzerg force-pushed the master branch from fcc0338 to bb14e57 Compare May 15, 2018 13:31

threeleafzerg changed the title ~~[MXNET-366]Extend MXNet Distributed Training by MPI AllReduce~~ [MXNET-366]Extend MXNet Distributed Training by AllReduce May 16, 2018

threeleafzerg mentioned this pull request May 17, 2018

How does sockeye support distributed multi-node training awslabs/sockeye#397

Closed

eric-haibin-lin removed their assignment May 23, 2018

Code modification according to macro and xcgoner's review comments.

9fa70f4

Retrigger jenkins

177bd02

Merge branch 'master' into master

17d440a

threeleafzerg requested a review from anirudh2290 as a code owner July 10, 2018 01:33

zhouhaiy added 3 commits July 10, 2018 15:55

1. Adapt for the change of pull interface

470cbbe

2. Change the implementation of allreduce kvstore's barrier

Fix cpplint check error

fb3aa9a

Retrigger jenkins

127b085

ctcyang mentioned this pull request Jul 13, 2018

[MXNET-331] Single machine All Reduce Topology-aware Communication (Updated) #11591

Merged

10 tasks

pengzhao-intel mentioned this pull request Aug 18, 2018

ImageIter crashing with 64k samples per batch #12240

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suleisl2000 mentioned this pull request Aug 31, 2018

Request for roadmap kubeflow/mxnet-operator#6

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threeleafzerg closed this Sep 7, 2018

NanYan1119 mentioned this pull request Sep 17, 2018

When the horovod can support MXNet for training by allreduce? ctcyang/incubator-mxnet#4

Closed

[MXNET-366]Extend MXNet Distributed Training by AllReduce #10696

[MXNET-366]Extend MXNet Distributed Training by AllReduce #10696

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