Explore @amplab Open Source projects

AMPLab at UC Berkeley (@amplab)

amplab

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shark

Development in Shark has been ended.

SparkNet

Distributed Neural Networks for Spark

keystone

Simplifying robust end-to-end machine learning on Apache Spark.

spark-ec2

Scripts used to setup a Spark cluster on EC2

graphx

Former GraphX development repository. GraphX has been merged into Apache Spark; please submit pull requests there.

snap

Scalable Nucleotide Alignment Program -- a fast and accurate read aligner for high-throughput sequencing data

succinct

Enabling queries on compressed data.

docker-scripts

Dockerfiles and scripts for Spark and Shark Docker images

spark-indexedrdd

An efficient updatable key-value store for Apache Spark

datascience-sp14

Repository for data science course Spring 14

MLI

An API for Distributed Machine Learning

training

Training materials for Strata, AMP Camp, etc

drizzle-spark

Drizzle integration with Apache Spark

carat

Carat: Collaborative Energy Debugging

velox-modelserver

benchmark

Large scale query engine benchmark

ml-matrix

Distributed Matrix Library

ampcrowd

A RESTful web service that runs microtasks across multiple crowds, provides quality control techniques, and is easily extensible.

smash

Benchmarking toolkit for variant calling

training-scripts

Scripts to launch cluster used for Strata

ernest

Code for Ernest

cyclades

succinct-cpp

ampcamp

scripts used for ampcamp

zipg

A Memory-efficient Graph Store for Interactive Queries

orchestra

Fine-Grained Distributed Computing

iolap

cs262a-fall2016

sprint

Sprint Transformations for RegEx queries

keystone-example

A example skeleton for an application built on top of KeystoneML

mlsys

An open source survey of the emerging systems for large-scale machine learning.

clipper-v0

ray-core

Experiments for the Ray backend

Buggypedia

sparse-covariance-inverse

siren-release

Public version of the SiRen project

keystone-integration-tests

Integration Tests for KeystoneML

ampcrowd-client-py

A python client for using the AMPCrowd service