# MaiterInc

**Repository Path**: ystraw/MaiterInc

## Basic Information

- **Project Name**: MaiterInc
- **Description**: 一个用于累计迭代计算的消息传递分布式框架，论文链接：https://www.researchgate.net/publication/265219392_Maiter_A_Message-Passing_Distributed_Framework_for_Accumulative_Iterative_Computation
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2020-09-02
- **Last Updated**: 2021-06-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

-- OVERVIEW

Maiter is implemented by modifying Piccolo.

-- PREREQUISITES

On debian/ubuntu, the required libraries can be acquired by running:

sudo apt-get install build-essential cmake g++ libboost-dev libboost-python-dev libboost-thread-dev liblzo2-dev libnuma-dev libopenmpi-dev libprotobuf-dev libcr-dev libibverbs-dev openmpi-bin protobuf-compiler liblapack-dev
 
the optional libraries can be install via:

sudo apt-get install libgoogle-perftools-dev python-dev swig

-- BUILDING

Simply run 'make', a runnable file 'maiter' will be appeared if build is successful.

-- RUNNING

To execute a Piccolo program, you will need to modify conf/mpi-cluster
to point to the set of machines Piccolo will be executed on - for example, a file
might look like:

localhost slots=1
a slots=4
b slots=4
c slots=4

Which would allow for running up to 12 workers (+ 1 master process).

The following is the script to run pagerank
---------------------------------------------
ALGORITHM=Pagerank
WORKERS=12
GRAPH=input/pr_graph
RESULT=result/pr
NODES=10000
SNAPSHOT=1
TERMTHRESH=0.0001
BUFMSG=10000
PORTION=1


./maiter --runner=$ALGORITHM --workers=$WORKERS --graph_dir=$GRAPH --result_dir=$RESULT --num_nodes=$NODES --snapshot_interval=$SNAPSHOT --portion=$PORTION --termcheck_threshold=$TERMTHRESH --bufmsg=$BUFMSG --v=0