Ligra is a lightweight framework for processing graphs in shared memory. It is particularly suited for implementing parallel graph traversal algorithms where only a subset of the vertices are processed in an iteration. The project was motivated by the fact that the largest publicly available real-world graphs all fit in shared memory. When graphs fit in shared-memory, processing them using Ligra can give performance improvements of up orders of magnitude compared to distributed-memory graph processing systems.

FALCONN is a library with algorithms for the nearest neighbor search problem. The algorithms in FALCONN are based on Locality-Sensitive Hashing (LSH), which is a popular class of methods for nearest neighbor search in high-dimensional spaces. The goal of FALCONN is to provide very efficient and well-tested implementations of LSH-based data structures.

The MIT Language Modeling (MITLM) toolkit is a set of tools designed for the efficient estimation of statistical n-gram language models involving iterative parameter estimation.  It achieves much of its efficiency through the use of a compact vector representation of n-grams.  Details of the data structure and associated algorithms can be found in the following paper: Bo-June (Paul) Hsu and James Glass.

KPart is a tool for partitioning the last-level cache (LLC) dynamically between co-running applications on an Intel multicore processor with way-partitioning support. KPart is designed to sidestep a key limitation of way-partitioning: coarse-grained partition sizes.

Caliper is a precise traffic generator based on the NetFPGA platform with highly-accurate packet injection times that can be easily integrated with various software-based traffic generation tools.