Mimir is a new implementation of MapReduce over MPI. Mimir inherits the core principles of existing MapReduce frameworks, such as MR-MPI, while redesigning the execution model to incorporate a number of sophisticated optimization techniques that achieve similar or better performance with significant reduction in the amount of memory used.

gmm_diag and gmm_full: C++ classes for multi-threaded Gaussian mixture models and Expectation-Maximisation

A distributed file system similar to Google File System (GFS).

MapReduce framework in C++. Supports multi-threading in shared memory models.

My programming practice from different fields.

C++ implementation of the MapReduce library to handle MapReduce tasks on a distributed system. This library handles worker failures and performs load balancing.

MapReduce framework with C++11

MapReduce implementation with POSIX threads ThreadPool

Operating System Projects; Fall01

Collection streaming utilities.

Distributed Graph Clustering using the experimental Thrill framework

C++ framework for Map/Reduce paradigm

Performance evaluation of Phoenix++ and MPI + OpenMP equi-join models for processing big data

Fault-tolerant distributed system in asynchronous C++

Implementations for Ceng334-Introduction to Operating Systems Course Assignments

Buyer-seller with socket programming, MapReduce genre counter with pipes, image processing with pthreads.

CS542200 Parallel Programming HW4. Implement MapReduce by MPI + Pthread.

Code for Distributed Systems course assignments

CUDA Map and Reduce in CPP

A grpc based mapreduce framework implementation