The Multicast/Reduction Network: A User's Guide to MRNet v2.1

Table of Contents

1. Introduction
2. Installing and Using MRNet
Supported Platforms and Compilers
System Requirements
Build Configuration
Compilation and Installation
Testing the Code
Bugs, Questions and Comments
3. MRNet Components and Abstractions
4. A Simple Example
The MRNet Interface
MRNet Instantiation
5. The MRNet C++ API Reference
Class Network
Class NetworkTopology
Class Communicator
Class Stream
Class Packet
6. MRNET Process-tree Topologies
Topology File Format
Topology File Generator
7. Adding New Filters
Defining an MRNet Filter
Fault-tolerant MRNet Filters
Creating and Using MRNet Filter Shared Object Files
A. MRNet Format Strings
B. MRNet Stream Performance Data
C. A Complete MRNet Example: Integer Addition
D. Environment Variables

List of Tables

B.1. Metric-Context Compatibility Matrix

List of Examples

4.1. MRNet Front-end Sample Code
4.2. MRNet Back-end Sample Code
C.1. A Complete MRNet Front-End
C.2. A Complete MRNet Back-End
C.3. An MRNet Filter: Integer Addition
C.4. An MRNet Topology File

Chapter 1. Introduction

MRNet is a customizable, high-throughput communication software system for parallel tools and applications with a master/slave architecture. MRNet reduces the cost of these tools' activities by incorporating a tree-based overlay network (TBON) of processes between the tool's front-end and back-ends. MRNet uses the TBON to distribute many important tool communication anc computation activities, reducing analysis time and keeping tool front-end loads manageable.

MRNet-based tools send data between front-end and back-ends on logical flows of data called streams. MRNet internal processes use filters to synchronize and aggregate data sent to the tool's front-end. Using filters to manipulate data in parallel as it passes through the network, MRNet can efficiently compute averages, sums, and other more complex aggregations on back-end data.

Several features make MRNet especially well-suited as a general facility for building scalable parallel tools:

  • Flexible organization. MRNet does not dictate the organization of the TBON. MRNet process organization is specified in a configuration file that can specify common network overlays like k-ary and k-nomial trees, or custom layouts tailored to the system(s) running the tool. For example, MRNet internal processes can be allocated to dedicated system nodes or co-located with tool back-end and application processes.
  • Scalable, flexible data aggregation. MRNet's built-in filters provide efficient computation of averages, sums, concatenation, and other common data reductions. Custom filters can be loaded dynamically into the network to perform tool-specific aggregation operations.
  • High-bandwidth communication. MRNet transfers data within the tool system using an efficient, packed binary representation. Zero-copy data paths are used whenever possible to reduce the cost of transferring data through internal processes.
  • Scalable multicast. As the number of back-ends increases, serialization when sending control requests limits the scalability of existing tools. MRNet supports efficient message multicast to reduce the cost of issuing control requests from the tool front-end to its back-ends.
  • Multiple concurrent data channels. MRNet supports multiple logical streams of data between tool components. Data aggregation and message multicast takes place within the context of a data stream, and multiple operations (both upward and downward) can be active simultaneously.

Chapter 2. Installing and Using MRNet

For this discussion, $MRNET_ROOT is the location of the top-level directory of the MRNet distribution and $MRNET_ARCH is a string describing the platform (OS and architecture) as discovered by autoconf. For the installation instructions, it is assumed that the current working directory is $MRNET_ROOT.

Supported Platforms and Compilers

MRNet has been developed to be highly portable; we expect it to run properly on all common Unix-based as well as Microsoft Windows platforms. This being said, we have successfully built and tested MRNet on the following systems:

  • i686-pc-linux-gnu
  • ia64-unknown-linux-gnu
  • x86_64-unknown-linux-gnu
  • powerpc64-unknown-linux-gnu
  • rs6000-ibm-aix5.2.0.0
  • sparc-sun-solaris2.8
  • i386-unknown-nt4.0 (MS Visual Studio 2005)

Our build system attempts to use native system compilers where appropriate.

System Requirements

Here we list the third party tools that MRNet uses and needs for proper installation on UNIX/Linux systems. For Windows systems, pre-compiled libraries and binaries are available (upon request).

  • GNU make
  • flex
  • bison (version 2.3 or later)

Build Configuration

MRNet uses GNU autoconf to discover the platform specific configuration parameters. The script that does this auto-configuration is called configure.

UNIX>  ./configure --help

shows all possible options of the command. Below, we display the MRNet-specific ones:

  --with-libfldir dir            Directory containing flex library

  --enable-shared                Build shared library versions of MRNet and XPlat

  --enable-debug                 Build MRNet and XPlat with debug information

  --enable-verbosebuild          Show build actions (useful for debugging build problems)

./configure without any options should give reasonable results, but the user may specify certain options. For example,

UNIX> ./configure CXX=g++ --with-libfldir=/usr/local/lib

instructs the configure script to use g++ for the C++ compiler and /usr/local/lib as the location of the flex library.

Compilation and Installation

To build MRNet:

UNIX>  make

After a successful build, the following files will be present:

  • $MRNET_ROOT/lib/$MRNET_ARCH/libmrnet.a: MRNet API library
  • $MRNET_ROOT/lib/$MRNET_ARCH/libxplat.a: A library that exports platform dependent routines to MRNet
  • $MRNET_ROOT/bin/$MRNET_ARCH/mrnet_commnode: MRNet internal communcation node
  • $MRNET_ROOT/bin/$MRNET_ARCH/mrnet_topgen: MRNet topology file generator

To build the MRNet tests:

UNIX>  make tests

builds the MRNet test files. In addition to those files above, you will also generate:

  • $MRNET_ROOT/bin/$MRNET_ARCH/*_[FE,BE]: MRNet test front-end and back-end programs
  • $MRNET_ROOT/bin/$MRNET_ARCH/ A shell script that runs the test programs and checks for errors in an automated fashion.
  • $MRNET_ROOT/lib/$MRNET_ARCH/ Shared object used in tests of dynamic filter loading.

To install the MRNet components (i.e., libraries, executables, and headers) to the directories specified during configure (default install locations are /usr/local/{bin,lib,include}):

UNIX>  make install

To install the MRNet tests:

UNIX>  make install-tests

If your system does not provide the C++ Boost headers (normally installed in /usr/include/boost), we provide the subset of Boost header files necessary for building MRNet. To install these headers:

UNIX>  make install-boost

Testing the Code

The shell script, is placed in the binary directory with the other executables during the building of the MRNet tests as described above. This script can be used to run the MRNet test programs and check their output for errors. The script is used as follows:
UNIX> [ -l | -r <hostfile> | -a <hostfile> ] [ -f <sharedobject> ]
The -l flag is used to run all tests using only topologies that create processes on the local machine. The -r flag runs tests using remote machines specified in the file whose name immediately follows this flag. To run test both locally and remotely, use the -a flag and specify a hostfile to use. To run the programs that test MRNet's ability to dynamically load filters, you must specify the absolute location of the shared object produced when the tests were built.


To successfully run all tests, the location of the MRNet binaries must be in the user's $PATH. For testing dynamic filters, the filesystem containing the shared object must be available to all the host machines participating in the test.

Bugs, Questions and Comments

MRNet is maintained primarily by the Paradyn Project, University of Wisconsin-Madison. Comments and feedback whether positive or negative are encouraged.

Please report bugs to

The MRNet webpage is

Chapter 3. MRNet Components and Abstractions

The MRNet distribution has two main components: libmrnet.a, a library that is linked into a tool's front-end and back-end components, and mrnet_commnode, a program that runs on intermediate nodes interposed between the application front-end and back-ends. libmrnet.a exports an API (See Chapter 5, The MRNet C++ API Reference) that enables I/O interaction between the front-end and groups of back-ends via MRNet. The primary purpose of mrnet_commnode is to distribute data processing functionality across multiple computer hosts and to implement efficient and scalable group communications. The following sub-sections describe the lower-level components of the MRNet API in more detail.


An MRNet end-point represents a tool or application process. In particular, they represent the back-end processes (i.e., leaf processes) in the tree overlay. The front-end can communicate in a unicast or multicast fashion with one or more of these end-points as described below.


MRNet uses communicators to represent groups of end-points. Like communicators in MPI, MRNet communicators provide a handle that identifies a set of end-points for point-to-point, multicast or broadcast communications. MPI applications typically have a non-hierarchical layout of potentially identical processes. In contrast, MRNet enforces a tree-like layout of all processes, rooted at the front-end. Accordingly, MRNet communicators are created and managed by the front-end, and communication is only allowed between a front-end and its back-ends. As such, back-ends cannot interact with each other directly using the MRNet API.


A stream is a logical channel that connects the front-end to the end-points of a communicator. All MRNet communication uses the stream abstraction. Streams carry data packets downstream, from the front-end toward the back-ends, and upstream, from the back-ends toward the front-end. Streams are expected to carry data of a specific type, allowing data aggregation operations to be associated with a stream. The type is specified using a format string (See Appendix A, MRNet Format Strings) similar to those used in C formatted I/O primitives (e.g., a packet whose data is described by the format string "%d %d %f %s" contains two integers followed by a float then a character string). MRNet expands the standard format string specification to allow for description of arrays.


Data aggregation is the process of merging multiple input data packets and transforming them into one or more output packets. Though it is not necessary for the aggregation to result in less or even different data, aggregations that reduce or modify data values are most common. MRNet uses data filters to aggregate data packets. Filters specify an operation to perform and the type of the data expected on the bound stream. Filter instances are bound to a stream at stream creation. MRNet uses two types of filters: synchronization filters and transformation filters. Synchronization filters organize data packets from downstream nodes into synchronized waves of data packets, while transformation filters operate on the synchronized data packets yielding one or more output packets. A distinction between synchronization and transformation filters is that synchronization filters are independent of the packet data type, but transformation filters operate on packets of a specific type.

Synchronization filters operate on data flowing upstream in the network, receiving packets one at a time and outputting packets only when the specified synchronization criteria has been met. Synchronization filters provide a mechanism to deal with the asynchronous arrival of packets from children nodes. The synchronizer collects packets and typically aligns them into waves, passing an entire wave onward at the same time. Therefore, synchronization filters do no data transformation and can operate on packets in a type-independent fashion. MRNet currently supports two synchronization modes:

  • Wait For All: wait for a packet from every child node (SFILTER_WAITFORALL)
  • Do Not Wait: output packets immediately (SFILTER_DONTWAIT)

Transformation filters can be used on both upstream and downstream data flows. Transformation filters input a group of synchronized packets, and combine data from multiple packets by performing an aggregation that yields one or more new data packets. Since transformation filters are expected to perform computational operations on data packets, there is a type requirement for the data packets to be passed to this type of filter: the data format string of the stream's packets and the filter must be the same. Transformation operations must be synchronous, but are able to maintain state from one execution to the next. MRNet provides several transformation filters that should be of general use:

  • Basic scalar operations on characters/integers/floats: minimum (TFILTER_MIN), maximum (TFILTER_MAX), summation (TFILTER_SUM), average (TFILTER_AVG)
  • Concatenation: operation that inputs n scalars and outputs a vector of length n of the same base type (TFILTER_ARRAY_CONCAT)

Chapter 7, Adding New Filters describes facilities for adding new user-defined transformation and synchronization filters.

Chapter 4. A Simple Example

The MRNet Interface

A complete description of the MRNet API is in Chapter 5, The MRNet C++ API Reference. This section offers a brief overview only. Using libmrnet.a, a tool can leverage a system of internal processes, instances of the mrnet_commnode program, as a communication substrate. After instantiation of the MRNet network (discussed in the section called “MRNet Instantiation”, the front-end and back-end processes are connected by the internal processes. The connection topology and host assignment of these processes is determined by a configuration file, thus the geometry of MRNet's process tree can be customized to suit the physical topology of the underlying hardware resources. While MRNet can generate a variety of standard topologies, users can easily specify their own topologies; see Chapter 6, MRNET Process-tree Topologies for further discussion.

The MRNet API contains Network, EndPoint, Communicator, and Stream objects that a tool's front-end and back-end use for communication. The Network object is used to instantiate the MRNet network and access EndPoint objects that represent available tool back-ends. The Communicator object is a container for groups of end-points, and Stream objects are used to send data to the EndPoints in a Communicator.

Example 4.1. MRNet Front-end Sample Code

   front_end_main(...) {
1.     Network * net;
2.     Communicator * comm;
3.     Stream * stream;
4.     PacketPtr packet;
5.     int tag = FirstApplicationTag;
6.     float result;

7.     net = new Network(topology_file, backend_exe, backend_argv);

8.     comm = net->get_BroadcastCommunicator( );

9.     stream = net->new_Stream(comm, TFILTER_SUM, SFILTER_WAITFORALL);

10.    stream->send(tag, "%d", SUM_INIT);

11.    stream->recv(&tag, packet)

12.    packet->unpack("%f", &result);

A simplified version of code from an example tool front-end is shown in Example 4.1, “MRNet Front-end Sample Code”. In the front-end code, after some variable definitions in lines 1-6, an instance of the MRNet network is created on line 7 using the topology specified in topology_file. In line 8, the newly created Network object is queried for an auto-generated broadcast communicator that contains all available end-points. In line 9, this Communicator is used to establish a Stream that will use a built-in filter that finds the summation of the data sent upstream. The front-end then sends one or more initialization messages to the backends; in our example code on line 10, we broadcast an integer initializer on the new stream. The tag parameter is an application-specific value denoting the nature of the message being transmitted. After the send operation, the front-end performs a blocking stream receive at line 11. This call returns a tag and a packet. Finally, line 12 calls unpack to deserialize the floating point value contained in packet.

Example 4.2. MRNet Back-end Sample Code

   back_end_main(int argc, char** argv) {
1.     Stream * stream;
2.     PacketPtr packet;
3.     int val, tag;
4.     float random_float = (float) random( );

5.     Network * net = new Network(argc,argv);

6.     net->recv(&tag, packet, &stream);

7.     packet->unpack("%d", &val );

8.     if( val == SUM_INIT )
9.         stream->send(tag, "%f", random_float);

Example 4.2, “MRNet Back-end Sample Code” shows the code for the back-end that reciprocates the actions of the front-end. Each tool back-end first connects to the MRNet network in line 5, using the back-end version of the Network constructor that receives its arguments via the program argument vector (argc/argv). While the front-end makes a stream-specific receive call, the back-ends use a stream-anonymous network receive that returns the tag sent by the front-end, the packet containing the actual data sent, and a stream object representing the stream that the front-end has established. Finally, each back-end sends a scalar floating point value upstream toward the front-end.

A complete example of MRNet code can be found below in Appendix C, A Complete MRNet Example: Integer Addition.

MRNet Instantiation

While conceptually simple, creating and connecting the internal processes is complicated by interactions with the various job scheduling systems. In the simplest environments, we can launch jobs manually using facilities like rsh or ssh. In more complex environments, it is necessary to submit all requests to a job management system. In this case, we are constrained by the operations provided by the job manager (and these vary from system to system). We currently support two modes of instantiating MRNet-based tools.

In the first mode of process instantiation, MRNet creates the internal and back-end processes, using the specified MRNet topology configuration to determine the hosts on which the components should be located. First, the front-end consults the configuration and uses a remote shell program to create internal processes for the first level of the communication tree on the appropriate hosts. Upon instantiation, the newly created processes establish a network connection to the process that created it. The first activity on this connection is a message from parent to child containing the portion of the configuration relevant to that child. The child then uses this information to begin instantiation of the sub-tree rooted at that child. When a sub-tree has been established, the root of that sub-tree sends a report to its parent containing the end-points accessible via that sub-tree. Each internal node establishes its children processes and their respective connections sequentially. However, since the various processes are expected to run on different compute nodes, sub-trees in different branches of the network are created concurrently, maximizing the efficiency of network instantiation.

In the second mode of process instantiation, MRNet relies on a process management system to create some or all of the MRNet processes. This mode accommodates tools that require their back-ends to create, monitor, and control other processes. For example, IBM's POE uses environment variables to pass information, such as the process' rank within the application's global MPI communicator, to the MPI run-time library in each application process. In cases like this, MRNet cannot provide back-end processes with the environment necessary to start MPI application processes. As a result, MRNet creates its internal processes recursively as in the first instantiation mode, but does not instantiate any back-end processes. MRNet then waits for the tool back-ends to be started by the process management system to ensure they have the environment needed to create application processes successfully. To allow back-ends to connect to the MRNet network, information such as process host names and connection port numbers must be provided to the back-ends. This information can be provided via the environment, using shared filesystems or other information services as available on the target system. To collect the necessary information, the front-end can use the MRNet API methods for discovering the network topology details. We show how to construct a tool that requires back-ends to be separately instantiated in $MRNET_ROOT/Examples/NoBackEndInstantiation.

Chapter 5. The MRNet C++ API Reference

All classes are included in the MRN namespace. For this discussion, we do not explicitly include reference to the namespace; for example, when we reference the class Network, we are implying the class MRN::Network.

In MRNet, there are five top-level classes: Network, NetworkTopology, Communicator, Stream, and Packet. The Network class primarily contains methods for instantiating and destroying MRNet process trees. The NetworkTopology class represents the interface for discovering details about the topology of an instantiated Network. Application back-ends are referred to as end-points, and the Communicator class is used to reference a group of end-points. A Communicator is used to establish a Stream for unicast, multicast, or broadcast communications via the MRNet infrastructure. The Packet class encapsulates the data packets that are sent on a Stream. The public members of these classes are detailed below.

Class Network

void Network::Network(topology,  
const char *  topology;
const char *  backend_exe;
const char **  backend_argv;
bool  rank_backends =true;
bool  using_memory_buffer =false;

The front-end constructor method that is used to instantiate the MRNet process tree. topology is the path to a configuration file that describes the desired process tree topology.

backend_exe is the path to the executable to be used for the application's back-end processes. backend_argv is a null terminated list of arguments to pass to the back-end application upon creation. If backend_exe is NULL, no back-end processes will be started, and the leaves of the topology specified by topology will be instances of mrnet_commnode.

rank_backends indicates whether the back-end process ranks should begin at 0, similar to MPI rank numbering, and defaults to true.

If using_memory_buffer is set to true (default is false), the topology parameter is actually a pointer to a memory buffer containing the topology specification, rather than the name of a file.

When this function completes without error, all MRNet processes specified in the topology will have been instantiated. You may use Network::has_error() to check for successful completion.

void Network::Network(argc,  
int  argc;
char **  argv;
The back-end constructor method that is used when the process is started due to a front-end Network instantiation. MRNet automatically passes the necessary information to the process using the program argument vector (argc/argv) by inserting it after the user-specified arguments.
void Network::Network(parent_hostname,  
const char *  parent_hostname;
Port  parent_port;
Rank  parent_rank;
const char *  my_hostname;
Rank  my_rank;

The back-end constructor method that is used to attach to an instantiated MRNet process tree, as is necessary when the back-end processes are not started as part of a front-end Network instantiation.

parent_hostname is the name of the host where the parent process is running. parent_port and parent_rank are the port number and rank of the parent process, respectively. Information about the tree processes to which back-ends should connect can be gathered by the front-end using the NetworkTopology object returned from Network::get_NetworkTopology.

my_hostname is the name of the host on which the back-end process is running, and my_rank is an arbitrary rank chosen by the back-end to not conflict with the ranks of existing tree processes.

void Network::~Network();

Network::~Network is used to tear down the MRNet process tree and clean up the Network object. The first action taken by the destructor is to invoke Network::shutdown_Network.

void Network::shutdown_Network();

Network::shutdown_Network is used to tear down the MRNet process tree. When this function is called, each node in the tree sends a control message to its immediate children informing them of the "shutdown network" request, and waits for confirmation. If the node is an internal process (i.e., mrnet_commnode), the process will then terminate. If the node is an application back-end, the process will terminate unless a separate call to Network::set_TerminateBackEndsOnShutdown has been made to request otherwise.
void Network::set_TerminateBackEndsOnShutdown(terminate); 
bool  terminate;
Network::set_TerminateBackEndsOnShutdown is used to control whether application back-end processes are terminated when the MRNet Network is shutdown. By default, back-end processes will be terminated. If this behavior is not desired, call this method with terminate set to false.

bool Network::has_error();

Network::has_error returns true if an error has occured during the last call to a Network method. Network::print_error can be used to print a message describing the exact error.
void Network::print_error(error_msg); 
const char *  error_msg;
Network::print_error prints a message to stderr describing the last error encountered during a Network method. It first prints the null-terminated string, error_msg followed by a colon then the actual error message followed by a newline.

std::string Network::get_LocalHostName();

Network::get_LocalHostName returns the name of the host on which the MRNet process is running.

Port Network::get_LocalPort();

Network::get_LocalPort returns the port at which the MRNet process can be contacted.

Rank Network::get_LocalRank();

Network::get_LocalRank returns the rank of the MRNet process.
int Network::load_FilterFunc(so_file,  
const char *  so_file;
const char *  func_name;

This method, used for loading new filter operations into the Network is conveniently similar to the conventional dlopen() facilities for opening a shared object and dynamically loading symbols defined within.

so_file is the path to a shared object file that contains the filter function to be loaded and func_name is the name of the function to be loaded.

On success, Network::load_FilterFunc returns the id of the newly loaded filter which may be used in subsequent calls to Network::new_Stream. A value of -1 is returned on failure.

int Network::recv(tag,  
int *  tag;
PacketPtr &  packet;
Stream **  stream;
bool  blocking =true;

Network::recv is used to invoke a stream-anonymous receive operation. Any packet available (addressed to any stream) will be returned (in roughly FIFO ordering) via the output parameters.

otag will be filled in with the integer tag value that was passed by the corresponding Stream::send() operation. packet is the packet that was received. A pointer to the Stream to which the packet was addressed will be returned in stream.

blocking is used to signal whether this call should block or return if data is not immediately available; it defaults to a blocking call.

A return value of -1 indicates an error, 0 indicates no packets were available, and 1 indicates success.

bool Network::enable_PerformanceData(metric,  
perfdata_metric_t  metric;
perfdata_context_t  context;
Network::enable_PerformanceData uses Stream::enable_PerformanceData to start the recording of performance data of the specified metric type for the given context on all streams. Returns true on success, false otherwise. Appendix B, MRNet Stream Performance Data describes the supported metric and context types. See Stream::enable_PerformanceData for additional details.
bool Network::disable_PerformanceData(metric,  
perfdata_metric_t  metric;
perfdata_context_t  context;
Network::disable_PerformanceData uses Stream::disable_PerformanceData to stop the recording of performance data of the specified metric type for the given context on all streams. Returns true on success, false otherwise. See Stream::disable_PerformanceData for additional details.
bool Network::collect_PerformanceData(results,  
std::map< int, rank_perfdata_map > &  results;
perfdata_metric_t  metric;
perfdata_context_t  context;
int  aggr_filter_id =TFILTER_ARRAY_CONCAT;
Network::collect_PerformanceData uses Stream::collect_PerformanceData to collect the performance data of the specified metric type for the given context on all streams. The performance data of each stream is passed through the transformation filter identified by aggr_filter_id. The data for all streams is stored within the map results, keyed by stream identifier. Returns true on success, false otherwise. See Stream::collect_PerformanceData for additional details.
void Network::print_PerformanceData(metric,  
perfdata_metric_t  metric;
perfdata_context_t  context;
Network::enable_PerformanceData uses Stream::print_PerformanceData to print recorded performance data of the specified metric type for the given context on all streams. Data is printed to the MRNet log files. See Stream::print_PerformanceData for additional details.
void Network::get_EventNotificationFd(etyp); 
EventType  etyp;

Network::get_EventNotificationFd returns a file descriptor that can be added to the read fd_set of select() to receive notification of interesting DATA, TOPOLOGY, or ERROR events.

etyp should be set to one of ERROR_EVENT, DATA_EVENT, or TOPOLOGY_EVENT. DATA_EVENT can be used by both front-end and back-end processes to provide notification that one or more data packets have been received. TOPOLOGY_EVENT and ERROR_EVENT can only be used by front-end processes, and provide notification when the front-end observes a change in NetworkTopology or an error, respectively.

When select() indicates that the file descriptor has data available, you should call Network::clear_EventNotificationFd before taking action on the notification. When notifications are no longer needed, use Network::close_EventNotificationFd

void Network::clear_EventNotificationFd(etyp); 
EventType  etyp;
This method resets the event notification file descriptor returned from Network::get_EventNotificationFd. etyp should be set to one of ERROR_EVENT, DATA_EVENT, or TOPOLOGY_EVENT.
void Network::close_EventNotificationFd(etyp); 
EventType  etyp;
This method closes the event notification file descriptor returned from Network::get_EventNotificationFd. etyp should be set to one of ERROR_EVENT, DATA_EVENT, or TOPOLOGY_EVENT.
void Network::get_DataSocketFds(fd_array,  
int **  fd_array;
unsigned int *  fd_array_size;
Network::get_DataSocketFds is deprecated and has been removed. See Network::get_EventNotificationFd for a description of how to receive notifications for DATA_EVENTs.

Class NetworkTopology

Instances of NetworkTopology are network specific, so they are created when a Network is instantiated. MRNet API users should not need to create their own NetworkTopology instances.

NetworkTopology * Network::get_NetworkTopology(); 
Network::get_NetworkTopology is used to retrieve a pointer to the underlying NetworkTopology instance of a Network.
unsigned int NetworkTopology::get_NumNodes(); 
This method returns the total number of nodes in the tree topology, including front-end, internal, and back-end processes.
NetworkTopology::Node * NetworkTopology::find_Node(node_rank); 
Rank  node_rank;
This method returns a pointer to the tree node with rank equal to node_rank, or NULL if not found.
NetworkTopology::Node * NetworkTopology::get_Root(); 
This method returns a pointer to the root node of the tree, or NULL if not found.
void NetworkTopology::get_Leaves(leaves); 
std::vector< NetworkTopology::Node * > &  leaves;
This method fills in the leaves vector with pointers to the leaf nodes in the topology. In the case where back-end processes are not started when the Network is instantiated, a front-end process can use this function to retrieve information about the leaf internal processes to which the back-ends should attach.
void NetworkTopology::get_BackEndNodes(nodes); 
std::set< NetworkTopology::Node * > &  nodes;
This method fills a set with pointers to all back-end process tree nodes.
void NetworkTopology::get_ParentNodes(nodes); 
std::set< NetworkTopology::Node * > &  nodes;
This method fills a set with pointers to all tree nodes that are parents (i.e., those nodes having at least one child).
void NetworkTopology::get_OrphanNodes(nodes); 
std::set< NetworkTopology::Node * > &  nodes;
This method fills a set with pointers to all tree nodes that have no parent due to a failure.
void NetworkTopology::get_TreeStatistics(num_nodes,  
unsigned int &  num_nodes;
unsigned int &  depth;
unsigned int &  min_fanout;
unsigned int &  max_fanout;
double &  avg_fanout;
double &  stddev_fanout;

This method provides users statistics about the tree topology by filling the supplied parameters.

num_nodes is the total number of tree nodes (same as the value returned by NetworkTopology::get_NumNodes), depth is the depth of the tree (i.e., the maximum path length from root to any leaf), min_fanout is the minimum number of children of any parent node, max_fanout is the maximum number of children of any parent node, avg_fanout is the average number of children across all parent nodes, and stddev_fanout is the standard deviation in number of children across all parent nodes.

void NetworkTopology::print_TopologyFile(filename); 
const char *  filename;
This method will create (or overwrite) the specified topology file filename using the current state of this NetworkTopology object.
void NetworkTopology::print_DOTGraph(filename); 
const char *  filename;
This method will create (or overwrite) the specified dot graph file filename using the current state of this NetworkTopology object.
std::string NetworkTopology::Node::get_HostName(); 
This method returns a character string identifying the hostname of the tree node.

Port NetworkTopology::Node::get_Port();

This method returns the connection port of the tree node.

Rank NetworkTopology::Node::get_Rank();

This method returns the unique rank of the tree node.
const std::set< NetworkTopology::Node * > & NetworkTopology::Node::get_Children(); 
This method returns a set containing pointers to the children of the tree node, and is useful for navigating through the tree.
unsigned int NetworkTopology::Node::get_NumChildren(); 
This method returns the number of children of the tree node.
unsigned int NetworkTopology::Node::find_SubTreeHeight(); 
This method returns the height of the subtree rooted at this tree node.

Class Communicator

Instances of Communicator are network specific, so their creation methods are functions of an instantiated Network object.

Communicator * Network::new_Communicator();

This method returns a pointer to a new Communicator object. The object initially contains no end-points. Use Communicator::add_EndPoint to populate the Communicator.
Communicator * Network::new_Communicator(comm); 
Communicator &  comm;
This method returns a pointer to a new Communicator object that initially contains the set of end-points contained in comm.
Communicator * Network::new_Communicator(endpoints); 
std::set< CommunicationNode * > &  endpoints;
This method returns a pointer to a new Communicator object that initially contains the set of end-points contained in endpoints.
Communicator * Network::get_BroadcastCommunicator(); 

This method returns a pointer to a default broadcast Communicator containing all the end-points available in the system at the time the function is called.

Multiple calls to this function return the same pointer to the broadcast communicator object created at network instantiation. If the Network's topology changes, as can occur when starting back-ends separately, the object will be updated to reflect the additions or deletions. This object should not be deleted.

bool Communicator::add_EndPoint(ep_rank); 
Rank  ep_rank;

This method is used to add an existing end-point with rank ep_rank to the set contained by the Communicator.

The original set of end-points contained by the Communicator is tested to see if it already contains the potentially new end-point. If so, the function silently returns successfully. This method fails if there exists no end-point defined by ep_rank. This method returns true on success, false on failure.

bool Communicator::add_EndPoint(endpoint); 
CommunicationNode *  endpoint;
This method is similar to the add_EndPoint() above except that it takes a pointer to a CommunicationNode object instead of a rank. Success and failure conditions are exactly as stated above. This method also returns true on success and false on failure.
const std::set< CommunicationNode * > & Communicator::get_EndPoints(); 
This method returns a reference to the set of CommunicationNode pointers comprising the end-points in the Communicator.
std::string CommunicationNode::get_HostName(); 
This method returns a character string identifying the hostname of the end-point represented by this CommunicationNode. is out of range.

Port CommunicationNode::get_Port();

This method returns the connection port of the end-point represented by this CommunicationNode.

Rank CommunicationNode::get_Rank();

This method returns the unique rank of the end-point represented by this CommunicationNode.

Class Stream

Instances of Stream are network specific, so their creation methods are functions of an instantiated Network object. There are two common approaches to creating a new stream.

Stream * Network::new_Stream(comm,  
Communicator *  comm;
int  up_transfilter_id =TFILTER_NULL;
int  up_syncfilter_id =SFILTER_WAITFORALL;
int  down_transfilter_id =TFILTER_NULL;

This version of Network::new_Stream() is the straightforward way to create a Stream object attached to the end-points specified by a Communicator object comm.

up_transfilter_id specifies the transformation filter to apply to data flowing upstream from the application back-ends toward the front-end; the default value is TFILTER_NULL.

up_syncfilter_id specifies the synchronization filter to apply to upstream packets; the default value is SFILTER_WAITFORALL.

down_transfilter_id allows the user to specify a filter to apply to downstream data flows; the default value is TFILTER_NULL.

Stream * Network::new_Stream(comm,  
Communicator *  comm;
std::string  us_filters;
std::string  sync_filters;
std::string  ds_filters;

This version of Network::new_Stream() allows the user to map arbitrary packet filters to arbitrary nodes within the tree. Like the simpler version of Network::new_Stream(), the end-points are specified by the comm argument.

Strings are used to express the filter mappings, with the following syntax: "filter_id_1 => node_rank_1; filter_id_2 => node_rank_2;". If "*" is specified as the rank for an assignment, the filter will be assigned to all ranks that have not already been assigned. If a rank within comm is not assigned a filter, it will use the default filter. See $MRNET_ROOT/Examples/HeterogeneousFilters for an example of using Network::new_Stream() to specify different filter types to be used within the same stream.

us_filters specifies the transformation filter(s) to apply to data flowing upstream from the application back-ends toward the front-end.

sync_filters specifies the synchronization filter(s) to apply to upstream packets.

ds_filters allows the user to specify a filter to apply to downstream data flows.

Note that more than one filter should not be assigned to a single node in any of these strings.

Stream * Network::get_Stream(iid); 
unsigned int  iid;
Network::get_Stream() returns a pointer to the Stream identified by id, or NULL on failure.

unsigned int Stream::get_Id();

This method returns the integer identifier for this Stream.
const std::set< Rank > & Stream::get_EndPoints(); 
This method returns the set of end-point ranks for this Stream.

unsigned int Stream::size();

This method returns an integer indicating the number of end-points for this Stream.
int Stream::send(tag,  
int  tag;
const char *  format_string;
This method invokes a data send operation on the calling Stream. tag is an integer identifier that is expected to classify the data in the packet to be transmitted across the Stream. format_string is a format string describing the data in the packet (See Appendix A, MRNet Format Strings for a full description.) On success, Stream::send() returns 0; on failure -1.


tag must have a value greather than or equal to the constant FirstApplicationTag defined by MRNet (#include "mrnet/Types.h"). Tag values less than FirstApplicationTag are reserved for internal MRNet use.
int Stream::recv(tag,  
int *  tag;
PacketPtr &  packet;
bool  blocking =true;

Stream::recv() invokes a stream-specific receive operation. Packets addressed to the calling stream will be returned in strictly FIFO ordering via the output parameters.

tag will be filled in with the integer tag value that was passed by the corresponding Stream::send() operation. packet is the recieved Packet.

blocking determines whether the receive should block or return if data is not immediately available; it defaults to a blocking call.

A return value of -1 indicates an error, 0 indicates no packets were available, and 1 indicates success.

int Stream::flush();

Commits a flush of all packets currently buffered by the stream pending an output operation. A successful return value of 1 indicates that all packets on the calling stream have been passed to the operating system for network transmission.
int Stream::set_FilterParameters(upstream,  
bool  upstream;
const char *  format_string;

Stream::set_FilterParameters allows users to dynamically configure the operation of a Stream transformation filter by passing arbitrary data in a similar fashion to Stream::send. When the filter executes, the passed data is available as a PacketPtr parameter to the filter, and the filter can extract the configuration settings.

When set to true, upstream indicates the upstream transformation filter should be updated, while a value of false will update the downstream transformation filter.

bool Stream::enable_PerformanceData(metric,  
perfdata_metric_t  metric;
perfdata_context_t  context;
Stream::enable_PerformanceData starts recording performance data for the specified metric type for the given context. Returns true on success, false otherwise. Appendix B, MRNet Stream Performance Data describes the supported metric and context types.
bool Stream::disable_PerformanceData(metric,  
perfdata_metric_t  metric;
perfdata_context_t  context;
Stream::disable_PerformanceData stops recording performance data for the specified metric type for the given context. Previously recorded data is not discarded, so that it can be retrieved with Stream::collect_PerformanceData. Users can enable/disable recording for a particular metric and context any number of times before collecting the results. Returns true on success, false otherwise.
bool Stream::collect_PerformanceData(results,  
rank_perfdata_map&  results;
perfdata_metric_t  metric;
perfdata_context_t  context;
int  aggr_filter_id =TFILTER_ARRAY_CONCAT;

Stream::collect_PerformanceData collects the recorded performance data for the specified metric type for the given context. The collected data is stored within a rank_perfdata_map, which associates individual Ranks to a std::vector< perf_data_t > containing the recorded data instances. After collection, the recorded data at each Rank is discarded. Returns true on success, false otherwise.

Users can aggregate the recorded data across Ranks by specifying a transformation filter with aggr_filter_id. Note that only the built-in filter types of TFILTER_SUM, TFILTER_MIN, TFILTER_MAX, TFILTER_AVG, and TFILTER_ARRAY_CONCAT are supported. By default, performance data from each Rank is concatenated, and results contains every recorded data instance for each Rank. If the summary aggregation filters are used, results will contain a single associated pair. The Rank for this pair is equal to -1*(number of aggregated ranks), and the vector contains one or more aggregated instances.

void Stream::print_PerformanceData(metric,  
perfdata_metric_t  metric;
perfdata_context_t  context;
Stream::print_PerformanceData prints recorded performance data of the specified metric type for the given context. At each Rank, the data is printed to the MRNet log files and then discarded.

Class Packet

A Packet encapsulates a chunk of formatted data sent on a Stream. Packets are created using a format string (e.g., "%s %d" describes a null-terminated string followed by a 32-bit integer, and the Packet is said to contain 2 data elements). MRNet front-end and back-end processes do not create instances of Packet; instead they are automatically produced from the formatted data passed to Stream::send. Appendix A, MRNet Format Strings contains the full listing of data types that can be sent in a Packet.

When receiving a Packet via Stream::recv or Network::recv, the Packet instance is stored within a PacketPtr object. PacketPtr is a class based on the Boost library shared_ptr class, and helps with memory management of Packets. A PacketPtr can be assumed to be equivalent to "Packet *", and all operations on Packets require use of PacketPtr.

int Packet::get_Tag();

This method returns the integer tag associated with the Packet.

unsigned short Packet::get_StreamId();

This method returns the stream id associated with the Packet.

const char * Packet::get_FormatString();

This method returns the character string specifying the data format of the Packet.
void Packet::unpack(format_string,  
const char *  format_string;
This method extracts data contained within a Packet according to the format_string, which must match that of the Packet. The function arguments following format_string should be pointers to the appropriate types of each data item. For string and array data types, new memory buffers to hold the data will be allocated using malloc(), and it is the user's responsibility to free() these strings and arrays.

void Packet::set_DestroyData(destroy, ...);
bool destroy;

This method can be used to tell MRNet whether or not to deallocate the string and array data members of a Packet. If destroy is true, string and array data members will be deallocated using free() when the Packet destructor is executed. Note this assumes they were allocated using malloc(). The default behavior for user-generated Packets is not to deallocate (false). Turning on deallocation is useful in filter code that must allocate strings or arrays for output Packets, which cannot be freed before the filter function returns.

Chapter 6. MRNET Process-tree Topologies

MRNet allows a tool to specify a node allocation and process connectivity tailored to its computation and communication requirements and to the system where the tool will run. Choosing an appropriate MRNet configuration can be difficult due to the complexity of the tool's own activity and its interaction with the system. This section describes how users define their own process topologies, and the mrnet_topgen utility provided by MRNet to facilitate the process.

Topology File Format

The first parameter to the Network::Network() front-end constructor is the name of an MRNet topology file. This file defines the topological layout of the front-end, internal nodes, and back-end MRNet processes. In the syntax of the topology file, the hostname:id tuple represents a process with a MRNet instance id running on hostname. It is important to note that the id is of symbolic value only and does not reflect a port or process number associated with the system. A line in the topology file is always of the form:

hostname1:0 => hostname1:1 hostname1:2 ;

meaning a process on hostname1 with MRNet id 0 has two children, with MRNet ids 1 and 2, running on the same host. MRNet will parse the topology file without error if the file properly defines a tree in the mathematical sense (i.e. a tree must have a single root, no cycles, full connection, and no node can be its own descendant).


A single topology specification line may span multiple physical lines to improve readability. For example:
   hostname1:0 => 


The hostname associated with the root of the topology must match the host where the front-end process is run.

Topology File Generator

When the MRNet test programs are built, a topology generator program, $MRNET_ROOT/bin/$MRNET_ARCH/mrnet_topgen, will also be created. The usage of this program is:


Create a MRNet topology from the machines listed in [INFILE],
or standard input, and writes output to [OUTFILE], or standard output.

The format of the input machine list is one machine specification per line,
where each specification is of the form "host[:num-processors]". Note that
the first machine listed should be the host where the front-end should be run.


         -m max-host-procs, --maxprocs=max-host-procs
                 Specify the maximum number of processes to place on any machine,
                 in which case the number of processes allocated to a machine will be
                 the minimum of its processor count and "max-host-procs".


         -b topology, --balanced=topology
                 Create a balanced tree using "topology" specification. The specification
                 is in the format F^D, where F is the fan-out (or out-degree) and D is the
                 tree depth. The number of tree leaves (or back-ends) will be F^D.
                 An alternative specification is FxFxF, where the fan-out at each level
                 is specified explicitly and can differ between levels.

                 Example: "16^3" is a tree of depth 3 with fan-out 16, with 4096 leaves.
                 Example: "2x4x8" is a tree of depth 3 with 64 leaves.

         -k topology, --knomial=topology
                 Create a k-nomial tree using "topology" specification. The specification
                 is in the format K@N, where K is the k-factor (≥2) and N is the total
                 number of tree nodes. The number of tree leaves (or back-ends) will be

                 Example: "2@128" is a binomial tree of 128 nodes, with 64 leaves.
                 Example: "3@27" is a trinomial tree of 27 nodes, with 18 leaves.

         -o topology, --other=topology
                 Create a generic tree using "topology" specification. The specification
                 for this option is (the agreeably complicated) N:N,N,N:... where N is
                 the number of children, ',' distinguishes nodes on the same level,
                 and ':' separates the tree into levels.

                 Example: "2:8,4" is a tree where the root has 2 children,
                          the 1st child has 8 children, and the
                          2nd child has 4 children.

Chapter 7. Adding New Filters

Defining an MRNet Filter

A filter function has the following signature:

void filter_name(packets_in,  
std::vector< PacketPtr > &  packets_in;
std::vector< PacketPtr > &  packets_out;
std::vector< PacketPtr > &  packets_out_reverse;
void **  filter_state;
PacketPtr &  config_params;

packets_in is a reference to a vector of Packets serving as input to the filter function. packets_out is a reference to a vector into which output Packets should be placed. In the rare case where Packets need to be sent in the reverse direction on the Stream, packets_out_reverse should be used instead of packets_out. filter_state may be used to define and maintain state specific to a filter instance. Finally, config_params is a reference to a PacketPtr containing the current configuration settings for the filter instance, as can be set using Stream::set_FilterParameters.

For each filter function defined in a shared object file, there must be a const char * symbol named by the string formed by the concatenation of the filter function name and the suffix "_format_string". For instance, if the filter function is named my_filter_func, the shared object must define a symbol const char *my_filter_func_format_string. The value of this string will be the MRNet format string describing the format of data that the filter can operate on. A value of "" denotes that the filter can operate on data of arbitrary value.

Fault-tolerant MRNet Filters

MRNet automatically recovers from failures of internal tree processes (i.e., those processes that are not the front-end (root) or back-ends (leaves)). As part of the recovery, MRNet will extract filter state from the children of a failed process and pass that state as input to each child's newly chosen parent. If you have a filter that maintains persistent state using filter_state, you can provide an additional function within the shared object for your filter that MRNet may use to extract the state. The name of this extraction function should be the same as the filter name with the suffix "_get_state" appended. For instance, if the filter function is named my_filter_func, the extraction function should be named my_filter_func_get_state.

A filter state extraction function has the following signature:

PacketPtr filter_name_get_state(filter_state,  
void **  filter_state;
int  stream_id;

filter_state is a pointer to the state defined by the filter for the given Stream identified by stream_id. This function should extract the necessary state and return a Packet that can be passed as input to the filter function. Since the Packet will be processed as a normal input Packet for the filter, it's format must match that expected by the filter. A fault-tolerant filter example is provided in $MRNET_ROOT/Examples/FaultRecovery.

Creating and Using MRNet Filter Shared Object Files

This topic currently pertains to use with the GNU C++ compiler only.

Since we use the C facility dlopen() to dynamically load new filter functions, all C++ symbols must be exported. That is, the symbol definitions must fall with the statements

extern "C" {



The file that contains the filter functions and format strings may be compiled with the GNU compiler options "-fPIC -shared -rdynamic" to produce a valid shared object.

Front-end and back-end programs that will dynamically load filters must be built with compiler options that notify the linker to export global symbols (for GNU compilers, you can use "-Wl,-E").

Appendix A. MRNet Format Strings

After the % character that introduces a conversion, there may be a number of flag characters. u, h, l, and a are special modifiers meaning unsigned, short, long and array, respectivley. The full set of conversions are:

c signed 8-bit character
uc unsigned 8-bit character
ac array of signed 8-bit characters
auc array of unsigned 8-bit characters
hd signed 16-bit decimal integer
uhd unsigned 16-bit decimal integer
ahd array of signed 16-bit decimal integers
auhd array of unsigned 16-bit decimal integers
d signed 32-bit decimal integer
ud unsigned 32-bit decimal integer
ad array of signed 32-bit decimal integers
aud array of unsigned 32-bit decimal integers
ld signed 64-bit decimal integer
uld unsigned 64-bit decimal integer
ald array of signed 64-bit decimal integers
auld array of unsigned 64-bit decimal integers
f 32-bit floating-point number
af array of 32-bit floating-point numbers
lf 64-bit floating-point number
alf array of 64-bit floating-point numbers
s null-terminated character string.
as array of null-terminated character strings.


All array format specifiers, "a*", require an extra implicit length parameter of type unsigned int to be specified. E.g., send("%d %af", integer_val, float_array_pointer, float_array_length)

Appendix B. MRNet Stream Performance Data

The primary abstraction for communication and data processing within MRNet is the stream, so performance metrics and contexts are associated with actions on a particular stream.

All data is recorded as instances of a perf_data_t, which is simply a union type that can hold a 64-bit signed integer, a 64-bit unsigned integer, or a double precision float. As shown below, the data values can be accessed using the i, u, or d union fields.

"typedef union { int64_t i; uint64_t u; double d; } perfdata_t;"

Metrics define the type of performance data to record. The supported metric types are:

  • PERFDATA_MET_NUM_BYTES: count of data bytes (uint64_t)
  • PERFDATA_MET_NUM_PKTS: count of data packets (uint64_t)
  • PERFDATA_MET_ELAPSED_SEC: elapsed seconds (double)
  • PERFDATA_MET_CPU_USR_PCT: percent CPU utilization by user (double)
  • PERFDATA_MET_CPU_USR_PCT: percent CPU utilization by system (double)
  • PERFDATA_MET_MEM_VIRT_KB: virtual memory footprint in KB (double)
  • PERFDATA_MET_MEM_PHYS_KB: physical memory footprint in KB (double)

Contexts specify when to record data. The supported contexts are:

  • PERFDATA_CTX_SEND: when data is sent
  • PERFDATA_CTX_RECV: when data is received
  • PERFDATA_CTX_FILT_IN: before executing transformation filter
  • PERFDATA_CTX_FILT_OUT: after executing transformation filter
  • PERFDATA_CTX_NONE: when data is collected

The following table shows which metrics are valid for a given context. When a metric is valid for only CTX_FILT_OUT, the metric is actually recorded through a combination of measurements at CTX_FILT_IN and CTX_FILT_OUT. When a metric is valid for only CTX_NONE, the data is only recorded at the time it is collected.

Table B.1. Metric-Context Compatibility Matrix



MET_CPU_USR_PCT, MET_CPU_SYS_PCT, MET_MEM_VIRT_KB, and MET_MEM_PHYS_KB are currently only supported for Linux.

An example MRNet application that makes use of the Stream performance data collection facilities is provided in $MRNET_ROOT/Examples/PerformanceData.

Appendix C. A Complete MRNet Example: Integer Addition

The source code for the example contained in this appendix can be found in $MRNET_ROOT/Examples/IntegerAddition. All examples can be built by typing 'make' from within the $MRNET_ROOT/Examples directory.

Example C.1. A Complete MRNet Front-End

#include "mrnet/MRNet.h"
#include "IntegerAddition.h"

using namespace MRN;

int main(int argc, char **argv)
    int send_val=32, recv_val=0;
    int tag, retval;
    PacketPtr p;

    if( argc != 4 ){
        fprintf(stderr, "Usage: %s topology_file backend_exe so_file\n", argv[0]);
    const char * topology_file = argv[1];
    const char * backend_exe = argv[2];
    const char * so_file = argv[3];
    const char * dummy_argv=NULL;

    // This Network() cnstr instantiates the MRNet internal nodes, according to the
    // organization in "topology_file," and the application back-end with any
    // specified cmd line args
    Network * network = new Network( topology_file, backend_exe, &dummy_argv  );

    // Make sure path to "so_file" is in LD_LIBRARY_PATH
    int filter_id = network->load_FilterFunc( so_file, "IntegerAdd" );
    if( filter_id == -1 ){
        fprintf( stderr, "Network::load_FilterFunc() failure\n");
        delete network;
        return -1;

    // A Broadcast communicator contains all the back-ends
    Communicator * comm_BC = network->get_BroadcastCommunicator( );

    // Create a stream that will use the Integer_Add filter for aggregation
    Stream * stream = network->new_Stream( comm_BC, filter_id,

    int num_backends = comm_BC->get_EndPoints().size();

    tag = PROT_SUM;
    unsigned int num_iters=5;
    // Broadcast a control message to back-ends to send us "num_iters"
    // waves of integers
    if( stream->send( tag, "%d %d", send_val, num_iters ) == -1 ){
        fprintf( stderr, "stream::send() failure\n");
        return -1;
    if( stream->flush( ) == -1 ){
        fprintf( stderr, "stream::flush() failure\n");
        return -1;

    // We expect "num_iters" aggregated responses from all back-ends
    for( unsigned int i=0; i<num_iters; i++ ){
        retval = stream->recv(&tag, p);
        assert( retval != 0 ); //shouldn't be 0, either error or block till data
        if( retval == -1){
            //recv error
            return -1;

        if( p->unpack( "%d", &recv_val ) == -1 ){
            fprintf( stderr, "stream::unpack() failure\n");
            return -1;

        if( recv_val != num_backends * i * send_val ){
            fprintf(stderr, "Iteration %d: Success! recv_val(%d) != %d*%d*%d=%d (send_val*i*num_backends)\n",
                    i, recv_val, send_val, i, num_backends, send_val*i*num_backends );
            fprintf(stderr, "Iteration %d: Success! recv_val(%d) == %d*%d*%d=%d (send_val*i*num_backends)\n",
                    i, recv_val, send_val, i, num_backends, send_val*i*num_backends );

    if(stream->send(PROT_EXIT, "") == -1){
        fprintf( stderr, "stream::send(exit) failure\n");
        return -1;
    if(stream->flush() == -1){
        fprintf( stderr, "stream::flush() failure\n");
        return -1;

    // The Network destructor will cause all internal and leaf tree nodes to exit
    delete network;

    return 0;

Example C.2. A Complete MRNet Back-End

#include "mrnet/MRNet.h"
#include "IntegerAddition.h"

using namespace MRN;

int main(int argc, char **argv)
    Stream * stream=NULL;
    PacketPtr p;
    int tag=0, recv_val=0, num_iters=0;

    Network * network = new Network( argc, argv );

        if ( network->recv(&tag, p, &stream) != 1){
            fprintf(stderr, "stream::recv() failure\n");
            return -1;

        case PROT_SUM:
            p->unpack( "%d %d", &recv_val, &num_iters );

            // Send num_iters waves of integers
            for( unsigned int i=0; i<num_iters; i++ ){
                if( stream->send(tag, "%d", recv_val*i) == -1 ){
                    fprintf(stderr, "stream::send(%%d) failure\n");
                    return -1;
                if( stream->flush( ) == -1 ){
                    fprintf(stderr, "stream::flush() failure\n");
                    return -1;

        case PROT_EXIT:
            fprintf( stdout, "Processing PROT_EXIT ...\n");

            fprintf(stdout, "Unknown Protocol: %d\n", tag);
    } while ( tag != PROT_EXIT );

    return 0;

Example C.3. An MRNet Filter: Integer Addition

extern "C" {

//Must Declare the format of data expected by the filter
const char * IntegerAdd_format_string = "%d"; 
void IntegerAdd( std::vector< PacketPtr > & packets_in,
                 std::vector< PacketPtr > & packets_out,
                 std::vector< PacketPtr > & /* packets_out_reverse */,
                 void ** /* client data */,
		 PacketPtr & /* params */ )
    int sum = 0;
    for( unsigned int i = 0; i < packets_in.size( ); i++ ) {
        PacketPtr cur_packet = packets_in[i];
	int val;
	cur_packet->unpack("%d", &val);
        sum += val;
    PacketPtr new_packet ( new Packet(packets_in[0]->get_StreamId(),
                                      packets_in[0]->get_Tag(), "%d", sum ) );
    packets_out.push_back( new_packet );

} /* extern "C" */

Example C.4. An MRNet Topology File

nutmeg:0 => c01:0 c02:0 c03:0 c04:0 ;

c03:0 => c05:0 ;

c04:0 => c06:0 c07:0 c08:0 c09:0 ;

c08:0 => c10:0 ;

c09:0 => c11:0 ;

#       nutmeg
#          |
#          |
#       -------
#       /|   |\
#      / |   | \
#     /  |   |  \
#    /   |   |   \
#  c01  c02  c03  c04
#             |    |
#            c05   |
#               -------
#              / |   | \
#             /  |   |  \
#            /   |   |   \
#          c06  c07 c08  c09
#                    |    |
#                   c10  c11 

Appendix D. Environment Variables

A number of environment variables are available to control the functionality of MRNet.

XPLAT_RSHSet this variable to the name of the remote shell program to use for remote process execution. Default is 'ssh'.
XPLAT_REMCMDIf it is necessary to run the remote shell program (XPLAT_RSH) with a utility such as runauth to non-interactively authenticate the unattended remote process, that command may be specified using this variable.
XPLAT_RESOLVE_HOSTSTell XPlat to perform DNS resolution of hostnames and IP addresses by setting the variable to '1'. Default is '1'.
XPLAT_RESOLVE_CANONICALWhen XPLAT_RESOLVE_HOSTS is '1', setting this variable to '1' will tell XPlat to try to resolve all hostnames to their canonical DNS format. Default is '0'.
MRNET_OUTPUT_LEVELSet the debug output level (valid values are 1-5, default is 1). Level 1 will only log warning/error messages, level 3 provides fairly detailed function execution logging, and level 5 will produce every log message that MRNet generates.
MRNET_DEBUG_LOG_DIRECTORYSpecify the absolute path to the directory to store MRNet log files generated by increasing MRNET_OUTPUT_LEVEL. If not set, the first existing directory from the following list is used:
  • $HOME/mrnet-log
  • $HOME
  • /tmp
MRN_COMM_PATHIf mrnet_commnode is not in your path by default, you can specify the full path using this variable.