[源码解析] 深度学习分布式训练框架 horovod (4) --- 网络基础 & Driver
[源码解析] 深度学习分布式训练框架 horovod (4) --- 网络基础 & Driver
目录
- [源码解析] 深度学习分布式训练框架 horovod (4) --- 网络基础 & Driver
Horovod 是Uber于2017年发布的一个易于使用的高性能的分布式训练框架，在业界得到了广泛应用。
本系列将通过源码分析来带领大家了解 Horovod。本文是系列第四篇，看看如何获取 host 之间的路由等网络信息。
前面几篇链接如下：
[源码解析] 深度学习分布式训练框架 Horovod (1) --- 基础知识
[源码解析] 深度学习分布式训练框架 horovod (2) --- 从使用者角度切入
[源码解析] 深度学习分布式训练框架 horovod (3) --- Horovodrun背后做了什么
在 horovod/runner/launch.py 文件中，_run_static 函数中使用 driver_service.get_common_interfaces 来获取路由信息等。
def _run_static(args):
nics = driver_service.get_common_interfaces(settings, all_host_names,
remote_host_names, fn_cache)因为这部分比较复杂（ Driver 的概念很类似 Spark 之中 Driver 的概念），所以本文我们单独来分析。
本文的分析问题点是：
- 为什么要知道路由信息？
- 当有多个host时候，horovod如何处理？
- 如何找到路由信息？
- 怎么互相交互？
- （后文会详细分析）SparkDriverService，SparkTaskService，ElasticDriver, Worker 都有什么区别和联系？
本文重点分析 HorovodRunDriverService 和 HorovodRunTaskService 相关。
先给出一个图例，大家可以有些概念。
从注释可知，get_common_interfaces 完成了获得路由信息（所有host之间的共有路由接口集合）的功能，主要是调用 _driver_fn 来完成相关工作。
def get_common_interfaces(settings, all_host_names, remote_host_names=None, fn_cache=None):
'''
Find the set of common and routed interfaces on all the hosts.
'''
# 得到远端host地址
if remote_host_names is None:
remote_host_names = network.filter_local_addresses(all_host_names)
if len(remote_host_names) > 0:
if settings.nics: # 如果参数有设定网络接口，就使用
# If args.nics is provided, we will use those interfaces. All the workers
# must have at least one of those interfaces available.
nics = settings.nics
else:
# Find the set of common, routed interfaces on all the hosts (remote
# and local) and specify it in the args to be used by NCCL. It is
# expected that the following function will find at least one interface
# otherwise, it will raise an exception.
local_host_names = set(all_host_names) - set(remote_host_names)
# 获取其他host的网络接口
nics = _driver_fn(all_host_names, local_host_names, settings, fn_cache=fn_cache)
else:
nics = get_local_interfaces(settings) # 获取本地的网络接口
return nics2.1 get_local_interfaces
此函数比较简单，目的是获取本地的网络接口。
def get_local_interfaces(settings):
# If all the given hosts are local, find the interfaces with address
# 127.0.0.1
nics = set()
for iface, addrs in net_if_addrs().items():
if settings.nics and iface not in settings.nics:
continue
for addr in addrs:
if addr.family == AF_INET and addr.address == '127.0.0.1':
nics.add(iface)
break
return nics2.2 _driver_fn
这是本文重点，获取其他host 的网络接口，_driver_fn 的作用是：
- 启动 service 服务；
- 使用 driver.addresses() 获取 Driver 服务的地址（使用
self._addresses = self._get_local_addresses()完成）； - 使用 _launch_task_servers（利用 Driver 服务的地址）在每个 worker 之中启动 task 服务，然后 task 服务会在 service 服务中注册；
- 因为是一个环形，每个 worker 会探测 worker index + 1 的所有网络接口；
- 最后 _run_probe 返回一个所有 workers 上的所有路由接口的交集；
代码如下：
这里需要注意的一点是：@cache.use_cache() 的使用：当第一次使用过之后，会把结果放入缓存。
@cache.use_cache()
def _driver_fn(all_host_names, local_host_names, settings):
"""
launches the service service, launches the task service on each worker and
have them register with the service service. Each worker probes all the
interfaces of the worker index + 1 (in a ring manner) and only keeps the
routed interfaces. Function returns the intersection of the set of all the
routed interfaces on all the workers.
:param all_host_names: list of addresses. for example,
['worker-0','worker-1']
['10.11.11.11', '10.11.11.12']
:type all_host_names: list(string)
:param local_host_names: host names that resolve into a local addresses.
:type local_host_names: set
:param settings: the object that contains the setting for running horovod
:type settings: horovod.runner.common.util.settings.Settings
:return: example: ['eth0', 'eth1']
:rtype: list[string]
"""
# Launch a TCP server called service service on the host running horovod
# 启动 service 服务
num_hosts = len(all_host_names)
driver = HorovodRunDriverService(num_hosts, settings.key, settings.nics)
# Have all the workers register themselves with the service service.
#（利用 Driver 服务的地址）在每个worker之中启动 task 服务，然后task服务会在 service 服务中注册
_launch_task_servers(all_host_names, local_host_names,
driver.addresses(), settings)
try:
# 返回一个所有 workers 上的所有路由接口的交集
return _run_probe(driver, settings, num_hosts)
finally:
driver.shutdown()2.3 获取路由接口
我们对 _run_probe 函数做进一步分析。
2.3.1 probe逻辑
_run_probe 函数就是当 所有 task 都启动，注册，probe 环中下一个worker 邻居完成 之后，得到 接口集合。
利用 wait_for_initial_registration 等待所有 task 完成注册；
对于所有 task，完成 task.notify_initial_registration_complete 通知；
利用 driver.wait_for_task_to_task_address_updates 等待 每一个 worker probe 完成；
利用 nics.intersection_update 得到接口集合；
def _run_probe(driver, settings, num_hosts):
# wait for all the hosts to register with the service service.driver.wait_for_initial_registration(settings.start_timeout) tasks = [ task_service.HorovodRunTaskClient( index, driver.task_addresses_for_driver(index), settings.key, settings.verbose) for index in range( num_hosts)] # Notify all the drivers that the initial registration is complete. for task in tasks: task.notify_initial_registration_complete() # Each worker should probe the interfaces of the next worker in a ring # manner and filter only the routed ones -- it should filter out # interfaces that are not really connected to any external networks # such as lo0 with address 127.0.0.1. driver.wait_for_task_to_task_address_updates(settings.start_timeout) # Determine a set of common interfaces for task-to-task communication. nics = set(driver.task_addresses_for_tasks(0).keys()) for index in range(1, num_hosts): nics.intersection_update( driver.task_addresses_for_tasks(index).keys()) return nics
2.3.2 等待函数
probe 利用 wait_for_initial_registration 等待所有 task 完成注册，具体等待函数如下：
def wait_for_initial_registration(self, timeout):
self._wait_cond.acquire()
try:
while len(self._all_task_addresses) < self._num_proc:
self._wait_cond.wait(timeout.remaining())
timeout.check_time_out_for('tasks to start')
finally:
self._wait_cond.release()
def wait_for_task_to_task_address_updates(self, timeout):
self._wait_cond.acquire()
try:
while len(self._task_addresses_for_tasks) < self._num_proc:
self._wait_cond.wait(timeout.remaining())
timeout.check_time_out_for(
'tasks to update task-to-task addresses')
finally:
self._wait_cond.release()前面提到，Horovod Driver 的概念很类似 Spark 之中 Driver 的概念。Spark应用程序运行时主要分为 Driver 和 Executor，Driver负载总体调度及UI展示，Executor负责Task运行。用户的Spark应用程序运行在Driver上（某种程度上说，用户的程序就是Spark Driver程序），经过Spark调度封装成一个个Task，再将这些Task信息发给Executor执行，Task信息包括代码逻辑以及数据信息，Executor不直接运行用户的代码。
对于 Horovod 来说：
- HorovodRunDriverService 就是 Driver 的实现类。
- HorovodRunTaskService 提供了 Task 部分服务功能，这些 task 需要注册到 HorovodRunDriverService 之中。
- 这套 driver & task 机制的底层由 "基础网络服务" 支撑。
所以我们就仔细分析下基础网络服务。
3.1 继承关系
首先给出继承关系，我们下面讲解的 Driver 服务由 HorovodRunDriverService 提供，Task 服务由HorovodRunTaskService 提供。
这两个类最终都继承了 network.BasicService。
network.BasicService
^ ^
| |
+-------------------+ +-------------+
| |
+ +
driver_service.BasicDriverService task_service.BasicTaskService
^ ^
| |
| |
| |
+ +
HorovodRunDriverService HorovodRunTaskService3.2 network.BasicService
BasicService 提供了一个网络服务器功能。即通过find_port函数构建了一个ThreadingTCPServer，对外提供服务。
class BasicService(object):
def __init__(self, service_name, key, nics):
self._service_name = service_name
self._wire = Wire(key)
self._nics = nics
self._server, _ = find_port(
lambda addr: socketserver.ThreadingTCPServer(
addr, self._make_handler()))
self._server._block_on_close = True
self._port = self._server.socket.getsockname()[1]
self._addresses = self._get_local_addresses()
self._thread = in_thread(target=self._server.serve_forever)3.2.1 创建Server
创建服务器代码如下，这里是搜索一个随机端口，然后设置：
def find_port(server_factory):
min_port = 1024
max_port = 65536
num_ports = max_port - min_port
start_port = random.randrange(0, num_ports)
for port_offset in range(num_ports):
try:
port = min_port + (start_port + port_offset) % num_ports
addr = ('', port)
server = server_factory(addr)
return server, port
except Exception as e:
pass
raise Exception('Unable to find a port to bind to.')3.2.2 Server功能
服务器就是基本的功能，比如获取本server地址，处理 ping，网络交互等。
def _make_handler(self):
server = self
class _Handler(socketserver.StreamRequestHandler):
def handle(self):
try:
req = server._wire.read(self.rfile)
resp = server._handle(req, self.client_address)
# A tuple is the usual response object followed by a utf8 text stream
if type(resp) == tuple:
(resp, stream) = resp
server._wire.write(resp, self.wfile)
server._wire.stream(stream, self.wfile)
else:
server._wire.write(resp, self.wfile)
except (EOFError, BrokenPipeError):
# Happens when client is abruptly terminated, don't want to pollute the logs.
pass
return _Handler
def _handle(self, req, client_address):
if isinstance(req, PingRequest):
return PingResponse(self._service_name, client_address[0])
raise NotImplementedError(req)
def _get_local_addresses(self):
result = {}
for intf, intf_addresses in psutil.net_if_addrs().items():
if self._nics and intf not in self._nics:
continue
for addr in intf_addresses:
if addr.family == socket.AF_INET:
if intf not in result:
result[intf] = []
result[intf].append((addr.address, self._port))
return result
def addresses(self):
return self._addresses.copy()
def shutdown(self):
self._server.shutdown()
self._server.server_close()
self._thread.join()
def get_port(self):
return self._port3.3 network.BasicClient
HorovodRunDriverClient 和 HorovodRunTaskClient 这两个类都继承了network.BasicClient。
network.BasicClient 的作用就是连接 network.BasicService，与其交互。即 network.BasicClient 是一个操作接口。
network.BasicClient
^ ^
| |
+------------------+ +---------------+
| |
+ |
+
driver_service.BasicDriverClient task_service.BasicTaskClient
^ ^
| |
| |
+ +
HorovodRunDriverClient HorovodRunTaskClient两个主要 API 如下：
3.3.1 _probe
_probe 获取 server 的网络接口。
def _probe(self, addresses):
result_queue = queue.Queue()
threads = []
for intf, intf_addresses in addresses.items():
for addr in intf_addresses:
thread = in_thread(target=self._probe_one, args=(intf, addr, result_queue))
threads.append(thread)
for t in threads:
t.join()
result = {}
while not result_queue.empty():
intf, addr = result_queue.get()
if intf not in result:
result[intf] = []
result[intf].append(addr)
return result3.3.2 发送消息
_send 的作用是给server发送消息。
def _send(self, req, stream=None):
"""
Sends the request and returns the response object.
Streaming data response is transferred to the optional stream parameter.
"""
# Since all the addresses were vetted, use the first one.
addr = list(self._addresses.values())[0][0]
return self._send_one(addr, req, stream)3.4 总结
我们可以看到，network.BasicService 会提供了一个server，这个 Service 都是通过 network.BasicClient 来访问。基于此，Horovod 的HorovodRunDriverService 和 HorovodRunTaskService 这两个类就可以互相交互，进行沟通。
Driver 服务由 HorovodRunDriverService 提供，其功能主要是维护维护各种 task 地址以及相应关系。具体各种 task 地址 就是 Task 服务 来注册的。
需要注意的是：HorovodRunDriverService 和 HorovodRunTaskService 都最终继承了 network.BasicService，他们之间可以是异地运行交互。
4.1 HorovodRunDriverService
HorovodRunDriverService 是对 BasicDriverService 的封装。
HorovodRunDriverClient 是 其 访问接口。
class HorovodRunDriverService(driver_service.BasicDriverService):
NAME = 'horovod driver service'
def __init__(self, num_hosts, key, nics):
super(HorovodRunDriverService, self).__init__(num_hosts,
HorovodRunDriverService.NAME,
key, nics)
class HorovodRunDriverClient(driver_service.BasicDriverClient):
def __init__(self, driver_addresses, key, verbose, match_intf=False):
super(HorovodRunDriverClient, self).__init__(
HorovodRunDriverService.NAME,
driver_addresses,
key,
verbose,
match_intf=match_intf)4.2 BasicDriverService
BasicDriverService基类 主要就是 维护各种 task 地址以及相应关系。
class BasicDriverService(network.BasicService):
def __init__(self, num_proc, name, key, nics):
super(BasicDriverService, self).__init__(name, key, nics)
self._num_proc = num_proc
self._all_task_addresses = {}
self._task_addresses_for_driver = {}
self._task_addresses_for_tasks = {}
self._task_index_host_hash = {}
self._task_host_hash_indices = {}
self._wait_cond = threading.Condition()这里的各种 task 地址就是 Task 服务 注册到 Driver 的数值。
可以看到里面有各种关于地址的变量，为了让大家理解这些变量的作用，对于每一个变量我们举例如下（这里有些变量是专门为 spark 设计，都放到基类里面有点奇怪）：
4.2.1 _all_task_addresses
本变量是记录了所有 task 的地址，变量举例如下：
self._all_task_addresses = {
1: {
'lo' : [('1.1.1.1', 12345)],
'eth0' : [('10.10.10.01', 12345)]
},
0: {
'lo' : [('2.2.2.2', 54321)],
'eth0' : [('10.10.10.02', 54321)]
}
}本变量由 task 调用 RegisterTaskRequest 来注册。
if isinstance(req, RegisterTaskRequest):
self._wait_cond.acquire()
try:
assert 0 <= req.index < self._num_proc
self._all_task_addresses[req.index] = req.task_addresses使用时候，有几个方式，举例如下：
比如 all_task_addresses 获取 self._all_task_addresses[index].copy() 来决定 ping /check 的下一个跳转。
4.2.2 _task_addresses_for_driver
本变量是记录了所有 task 的地址，但是网卡接口有多种，这里选择与 本 driver 地址匹配的地址。
变量举例如下：
self._task_addresses_for_driver = {
1: {
'eth0' : [('10.10.10.01', 12345)]
},
0: {
'eth0' : [('10.10.10.02', 54321)]
}
}本变量由 task 调用 RegisterTaskRequest 来注册。
# Just use source address for service for fast probing.
self._task_addresses_for_driver[req.index] = \
self._filter_by_ip(req.task_addresses, client_address[0])具体使用举例如下：
def task_addresses_for_driver(self, index):
self._wait_cond.acquire()
try:
return self._task_addresses_for_driver[index].copy()
finally:
self._wait_cond.release()driver用这个地址来生成 其内部 task 变量。
tasks = [
task_service.HorovodRunTaskClient(
index,
driver.task_addresses_for_driver(index),
settings.key,
settings.verbose) for index in range(
num_hosts)]4.2.3 _task_addresses_for_tasks
该变量举例如下：
self._task_addresses_for_tasks = {
1: {
'eth0' : [('10.10.10.01', 12345)]
},
0: {
'eth0' : [('10.10.10.02', 54321)]
}
}本变量由RegisterTaskToTaskAddressesRequest注册。
if isinstance(req, RegisterTaskToTaskAddressesRequest):
self.register_task_to_task_addresses(req.index, req.task_addresses)
return network.AckResponse()
def register_task_to_task_addresses(self, index, task_addresses):
self._wait_cond.acquire()
try:
assert 0 <= index < self._num_proc
self._task_addresses_for_tasks[index] = task_addresses # 这里赋值
finally:
self._wait_cond.notify_all()
self._wait_cond.release()该变量被 task 用来获取 某个 task 的一套网络接口，比如：
# Determine a set of common interfaces for task-to-task communication.
nics = set(driver.task_addresses_for_tasks(0).keys())4.2.4 _task_index_host_hash
每一个 task 有一个对应的 host hash，该数值被 MPI 作为 host name 来操作。
self._task_index_host_hash = {
1: {
'ip-10-10-10-01-dfdsfdsfdsfdsf2'
},
0: {
'ip-10-10-10-02-treterwrtqwer'
}
}具体使用如下。这个函数是 spark 相关会使用，具体是逐一通知 spark task 进入下一阶段。
def task_indices(self):
self._wait_cond.acquire()
try:
return list(self._task_index_host_hash.keys())
finally:
self._wait_cond.release()或者使用如下，是为了获取某一个 host 对应的 host hash name。
def task_index_host_hash(self, index):
self._wait_cond.acquire()
try:
assert 0 <= index < self._num_proc
return self._task_index_host_hash[index]
finally:
self._wait_cond.release()4.2.5 _task_host_hash_indices
该变量举例如下：
self._task_host_hash_indices = {
{
'ip-10-10-10-01-dfdsfdsfdsfdsf2' : [1]
},
{
'ip-10-10-10-02-treterwrtqwer' : [0]
}
}具体是在注册 RegisterTaskRequest 时候生成。
self._task_host_hash_indices[req.host_hash].append(req.index)使用具体代码是：
def task_host_hash_indices(self):
self._wait_cond.acquire()
try:
return self._task_host_hash_indices.copy()
finally:
self._wait_cond.release()具体是被 rsh 使用。rsh 就是在某一个 host 上，让某一个 horovod rank 启动。具体逻辑是：
获取某一个 host 上所有的 task indices ；
利用 task_host_hash_indices 取出本进程 local rank 对应的 task index；
取出在 driver 中 task index 对应保持的 task address；
最后依据这个 task addresses 生成一个 SparkTaskClient，进行后续操作。
driver_client = driver_service.SparkDriverClient(driver_addresses, key, verbose=verbose)
task_indices = driver_client.task_host_hash_indices(host_hash)
task_index = task_indices[local_rank]
task_addresses = driver_client.all_task_addresses(task_index)
task_client = task_service.SparkTaskClient(task_index, task_addresses, key, verbose=verbose)
task_client.stream_command_output(stdout, stderr)
task_client.run_command(command, env,
capture_stdout=stdout is not None,
capture_stderr=stderr is not None,
prefix_output_with_timestamp=prefix_output_with_timestamp)
4.3 总体逻辑
总体逻辑如下：
network.BasicService
^ ^
| |
+-------------------+ +-------------+
| |
+ +
driver_service.BasicDriverService task_service.BasicTaskService
^ ^
| |
| |
| |
| +
+----------------+------------------+ HorovodRunTaskService
| HorovodRunDriverService |
| |
| |
| _all_task_addresses |
| |
| _task_addresses_for_driver |
| |
| _task_addresses_for_tasks |
| |
| _task_index_host_hash |
| |
| _task_host_hash_indices |
| |
+-----------------------------------+HorovodRunTaskService 提供了 Task 部分服务功能。整体逻辑是由几个函数共同完成。
5.1 启动具体服务
_launch_task_servers 用来启动具体服务，其主要作用是：多线程运行，在每一个线程中，远程运行 horovod.runner.task_fn。
其中：
- 传入参数中，all_host_names 就是程序启动时候配置的所有host，比如 ["1.1.1.1", "2.2.2.2"]；
- 使用了我们之前提到的 safe_shell_exec.execute 完成了安全运行保证；
- 使用我们前文提到的 get_remote_command 完成了远程命令的获取，即在命令之前加上了
ssh -o PasswordAuthentication=no -o StrictHostKeyChecking=no等等配置； - 最终每个启动的命令举例如下：
ssh -o PasswordAuthentication=no -o StrictHostKeyChecking=no 1.1.1.1 python -m horovod.runner.task_fn xxxxxxx； - 使用 execute_function_multithreaded 在每一个 host 上运行，启动 task 服务；
具体代码如下：
def _launch_task_servers(all_host_names, local_host_names, driver_addresses,
settings):
"""
Executes the task server and service client task for registration on the
hosts.
:param all_host_names: list of addresses. for example,
['worker-0','worker-1']
['10.11.11.11', '10.11.11.12']
:type all_host_names: list(string)
:param local_host_names: names that are resolved to one of the addresses
of local hosts interfaces. For example,
set(['localhost', '127.0.0.1'])
:type local_host_names: set
:param driver_addresses: map of interfaces and their address and port for
the service. For example:
{
'lo': [('127.0.0.1', 34588)],
'docker0': [('172.122.10.1', 34588)],
'eth0': [('11.111.33.73', 34588)]
}
:type driver_addresses: map
:param settings: the object that contains the setting for running horovod
:type settings: horovod.runner.common.util.settings.Settings
:return:
:rtype:
"""
def _exec_command(command):
host_output = io.StringIO()
try:
# 完成了安全运行保证
exit_code = safe_shell_exec.execute(command,
stdout=host_output,
stderr=host_output)
finally:
host_output.close()
return exit_code
args_list = []
num_hosts = len(all_host_names)
for index in range(num_hosts):
host_name = all_host_names[index] # all_host_names 就是程序启动时候配置的所有host，比如 ["1.1.1.1", "2.2.2.2"]
command = \
'{python} -m horovod.runner.task_fn {index} {num_hosts} ' \
'{driver_addresses} {settings}' \
.format(python=sys.executable,
index=codec.dumps_base64(index),
num_hosts=codec.dumps_base64(num_hosts),
driver_addresses=codec.dumps_base64(driver_addresses),
settings=codec.dumps_base64(settings))
if host_name not in local_host_names:
# 完成了远程命令的获取，即在命令之前加上了 `ssh -o PasswordAuthentication=no -o StrictHostKeyChecking=no`等等配置
command = get_remote_command(command,
host=host_name,
port=settings.ssh_port,
identity_file=settings.ssh_identity_file)
args_list.append([command])
# Each thread will use ssh command to launch the server on one task. If an
# error occurs in one thread, entire process will be terminated. Otherwise,
# threads will keep running and ssh session -- and the the task server --
# will be bound to the thread. In case, the horovod process dies, all
# the ssh sessions and all the task servers will die as well.
# 使用 execute_function_multithreaded 在每一个 host 上运行，启动 task 服务
threads.execute_function_multithreaded(_exec_command,
args_list,
block_until_all_done=False)5.2 具体服务逻辑
上段有：{python} -m horovod.runner.task_fn {index} {num_hosts} {driver_addresses} {settings}执行具体服务逻辑，所以我们介绍下 horovod.runner.task_fn。
_task_fn 函数完成了
- 生成了 HorovodRunTaskService 实例，赋值给 task；
- 使用
HorovodRunDriverClient . register_task来向 Driver 服务注册task（自己）的地址； - 使用
HorovodRunDriverClient . register_task_to_task_addresses来向 Driver 服务注册自己在Ring上 下一个邻居的地址； - 每一个 task 都做这个操作，最后就得到了在这个 ring cluster 之中的一个路由接口；
具体代码如下：
def _task_fn(index, num_hosts, driver_addresses, settings):
task = task_service.HorovodRunTaskService(index, settings.key, settings.nics)
try:
driver = driver_service.HorovodRunDriverClient(
driver_addresses, settings.key, settings.verbose)
# 向 Driver 服务注册task（自己）的地址
driver.register_task(index,
task.addresses(),
host_hash.host_hash())
task.wait_for_initial_registration(settings.start_timeout)
# Tasks ping each other in a circular fashion to determine interfaces
# reachable within the cluster.
next_task_index = (index + 1) % num_hosts
next_task_addresses = driver.all_task_addresses(next_task_index)
# We request interface matching to weed out all the NAT'ed interfaces.
next_task = task_service.HorovodRunTaskClient(
next_task_index,
next_task_addresses,
settings.key,
settings.verbose,
match_intf=True,
attempts=10)
# 向 Driver 服务注册自己在Ring上 下一个邻居的地址
driver.register_task_to_task_addresses(next_task_index,
next_task.addresses())
# Notify the next task that the address checks are completed.
next_task.task_to_task_address_check_completed()
# Wait to get a notification from previous task that its address checks
# are completed as well.
task.wait_for_task_to_task_address_check_finish_signal(settings.start_timeout)
finally:
task.shutdown()
if __name__ == '__main__':
index = codec.loads_base64(sys.argv[1])
num_hosts = codec.loads_base64(sys.argv[2])
driver_addresses = codec.loads_base64(sys.argv[3])
settings = codec.loads_base64(sys.argv[4])
_task_fn(index, num_hosts, driver_addresses, settings)5.3 HorovodRunTaskService
HorovodRunTaskService 主要的作用是提供了两个等待函数。因为具体路由操作是需要彼此通知，所以需要互相等待。
class HorovodRunTaskService(task_service.BasicTaskService):
NAME_FORMAT = 'horovod task service #%d'
def __init__(self, index, key, nics):
super(HorovodRunTaskService, self).__init__(
HorovodRunTaskService.NAME_FORMAT % index,
index, key, nics)
self.index = index
self._task_to_task_address_check_completed = False
def _handle(self, req, client_address):
if isinstance(req, TaskToTaskAddressCheckFinishedSignal):
self._wait_cond.acquire()
try:
self._task_to_task_address_check_completed = True
finally:
self._wait_cond.notify_all()
self._wait_cond.release()
return TaskToTaskAddressCheckFinishedSignalResponse(self.index)
return super(HorovodRunTaskService, self)._handle(req, client_address)
def wait_for_task_to_task_address_check_finish_signal(self, timeout):
self._wait_cond.acquire()
try:
while not self._task_to_task_address_check_completed:
self._wait_cond.wait(timeout.remaining())
timeout.check_time_out_for('Task to task address check')
finally:
self._wait_cond.release()
class HorovodRunTaskClient(task_service.BasicTaskClient):
def __init__(self, index, task_addresses, key, verbose, match_intf=False, attempts=3):
super(HorovodRunTaskClient, self).__init__(
HorovodRunTaskService.NAME_FORMAT % index,
task_addresses, key, verbose,
match_intf=match_intf,
attempts=attempts)
self.index = index
def task_to_task_address_check_completed(self):
resp = self._send(TaskToTaskAddressCheckFinishedSignal(self.index))
return resp.index逻辑如下：
_driver_fn
+
|
|
+---------------------------------------+-------------------------------------v
| |
| v
| _launch_task_servers
v +
driver = HorovodRunDriverService |
+ +--------------+-------------------+
| | |
| | |
v v v
+-------------------+---------------+ horovod.runner.task_fn ...... horovod.runner.task_fn
| HorovodRunDriverService | + +
| | | |
| | | |
| _all_task_addresses | | |
| | v v
| _task_addresses_for_driver | register_task +-----------+---------------+ +-------+--------------------+
| | | HorovodRunTaskService | | HorovodRunTaskService |
| _task_addresses_for_tasks | <--------------------------------+ | | |
| | | | wait | |
| _task_index_host_hash | | | <------> | |
| | <--------------------------------+ | | |
| _task_host_hash_indices | register_task_to_task_addresses | | | |
| | +---------------------------+ +----------------------------+
+-----------------------------------+ `手机如下：
本文总结如下：
- 因为 Horovod 分布式训练 涉及到多个 hosts，所以如果要彼此访问，需要知道路由信息；
- 当所有 task 都启动，注册，probe 环中下一个worker 邻居完成 之后，DriverService 会得到路由信息（所有host之间的共有路由接口集合），返回给 Horovod 主体部分使用；
- network.BasicService 提供了网络服务功能；
- XXXService 都是通过 XXXClient作为接口才能访问；
- HorovodRunDriverService 和 HorovodRunTaskService 都最终继承了 network.BasicService，他们之间可以是异地运行交互。
- HorovodRunTaskService 提供了 Task 部分服务功能，这些 task 需要注册到 Driver 之中（和Spark思路类似）。
- HorovodRunDriverService 是对 BasicDriverService 的封装。BasicDriverService 就是 维护各种 task 地址以及相应关系，比如：
- _all_task_addresses ：记录了所有 task 的地址；
- _task_addresses_for_driver ：记录了所有 task 的地址，但是因为网卡接口有多种，这里选择与 本driver 地址匹配的地址；
- _task_addresses_for_tasks ：用来给某一个 task 分配一个地址，同时获取本 task 的一套网络接口；
- _task_index_host_hash ：每一个 task 有一个对应的 host hash。这个函数是 spark 相关会使用，具体是逐一通知 spark task 进入下一阶段。或者是为了获取某一个 host 对应的 host hash name；
- _task_host_hash_indices ：具体是被 rsh 使用，由 rank 得到 在 driver 中 task index 对应保持的 task address；
- SparkDriverService，SparkTaskService，ElasticDriver, Worker 都有什么区别和联系？
- HorovodRunDriverService 这里只是用来得到路由信息，记录各种 Task 地址；
- SparkDriverService 除了记录路由和地址之外，还提交执行任务（Command），因为具体在哪一个Spark Executor启动之后，SparkDriverService 就需要知道 对应 SparkTaskService 的地址，这样才能知道提交到哪里；
- SparkTaskService 负责执行命令（抛弃了Spark Executor的逻辑，自己搞了一套），就是从 SparkDriverService 那里获得训练函数，然后启动 python 进程来执行；
- ElasticDriver 做得更多，因为还有弹性，需要容错；
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[源码解析] 深度学习分布式训练框架 Horovod (1) --- 基础知识
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