内容简介:An IPC library that uses the system's shared memory to pass messages. The communication paradigm is either publish-subscibe or RPC similar to ROS and ROS2. The library was built to be used withinRequired packages: Boost, MsgpackMessage Definition (
Shadesmar
An IPC library that uses the system's shared memory to pass messages. The communication paradigm is either publish-subscibe or RPC similar to ROS and ROS2. The library was built to be used within Project MANAS .
Required packages: Boost, Msgpack
Features
-
Multiple subscribers and publishers.
-
Multithreaded RPC support.
-
Uses a circular buffer to pass messages between processes.
-
Faster than using the network stack like in the case with ROS.
-
Read and write directly from GPU memory to shared memory.
-
Decentralized, without resource starvation .
-
Allows for both serialized message passing (using
msgpack
) and to pass raw bytes. -
No need to define external IDL files for messages. Use C++ classes as message definition.
Publish-Subscribe (serialized messages)
Message Definition ( custom_message.h
):
#include <shadesmar/message.h> class InnerMessage : public shm::BaseMsg { public: int inner_val{}; std::string inner_str{}; SHM_PACK(inner_val, inner_str); InnerMessage() = default; }; class CustomMessage : public shm::BaseMsg { public: int val{}; std::vector<int> arr; InnerMessage im; SHM_PACK(val, arr, im); explicit CustomMessage(int n) { val = n; for (int i = 0; i < 1000; ++i) { arr.push_back(val); } } // MUST BE INCLUDED CustomMessage() = default; };
Publisher:
#include <shadesmar/pubsub/publisher.h> #include <custom_message.h> int main() { shm::pubsub::Publisher<CustomMessage, 16 /* buffer size */ > pub("topic_name"); CustomMessage msg; msg.val = 0; for (int i = 0; i < 1000; ++i) { msg.init_time(shm::SYSTEM); // add system time as the timestamp p.publish(msg); msg.val++; } }
Subscriber:
#include <iostream> #include <shadesmar/pubsub/subscriber.h> #include <custom_message.h> void callback(const std::shared_ptr<CustomMessage>& msg) { std::cout << msg->val << std::endl; } int main() { shm::pubsub::Subscriber<CustomMessage, 16 /* buffer size */ > sub("topic_name", callback); // Using `spinOnce` with a manual loop while(true) { sub.spinOnce(); } // OR // Using `spin` sub.spin(); }
Publish-Subscribe (raw bytes)
Publisher:
#include <shadesmar/memory/copier.h> #include <shadesmar/pubsub/publisher.h> int main() { shm::memory::DefaultCopier cpy; shm::pubsub::PublisherBin<16 /* buffer size */ > pub("topic_name", &cpy); const uint32_t data_size = 1024; void *data = malloc(data_size); for (int i = 0; i < 1000; ++i) { p.publish(msg, data_size); } }
Subscriber:
#include <shadesmar/memory/copier.h> #include <shadesmar/pubsub/subscriber.h> void callback(shm::memory::Ptr *msg) { // `msg->ptr` to access `data` // `msg->size` to access `size` // The memory will be free'd at the end of this callback. // Copy to another memory location if you want to persist the data. // Alternatively, if you want to avoid the copy, you can call // `msg->no_delete()` which prevents the memory from being deleted // at the end of the callback. } int main() { shm::memory::DefaultCopier cpy; shm::pubsub::SubscriberBin<16 /* buffer size */ > sub("topic_name", &cpy, callback); // Using `spinOnce` with a manual loop while(true) { sub.spinOnce(); } // OR // Using `spin` sub.spin(); }
RPC
Server:
#include <shadesmar/rpc/server.h> int add(int a, int b) { return a + b; } int main() { shm::rpc::Function<int(int, int)> rpc_fn("add_fn", add); while (true) { rpc_fn.serve_once(); } // OR... rpc_fn.serve(); }
Client:
#include <shadesmar/rpc/client.h> int main() { shm::rpc::FunctionCaller rpc_fn("add_fn"); std::cout << rpc_fn(4, 5).as<int>() << std::endl; }
Note:
-
shm::pubsub::Subscriber
has a boolean parameter calledextra_copy
.extra_copy=true
is faster for smaller (<1MB) messages, andextra_copy=false
is faster for larger (>1MB) messages. For message of 10MB, the throughput forextra_copy=false
is nearly 50% more thanextra_copy=true
. See_read_with_copy()
and_read_without_copy()
ininclude/shadesmar/pubsub/topic.h
for more information. -
queue_size
must be powers of 2. This is due to the underlying shared memory allocator which uses a red-black tree. Seeinclude/shadesmar/memory/allocator.h
for more information. -
You may get this error while publishing:
Increase max_buffer_size
. This occurs when the default memory allocated to the topic buffer cannot store all the messages. The default buffer size for every topic is 256MB. You can access and modifyshm::memory::max_buffer_size
. The value must be set before creating a publisher.
以上所述就是小编给大家介绍的《Shadesmar -- Fast C++ IPC using shared memory》,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持!
猜你喜欢:本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们。
Learn Python 3 the Hard Way
Zed A. Shaw / Addison / 2017-7-7 / USD 30.74
You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring t......一起来看看 《Learn Python 3 the Hard Way》 这本书的介绍吧!
JSON 在线解析
在线 JSON 格式化工具
Markdown 在线编辑器
Markdown 在线编辑器