LSDPO - R244
review_log
Open Source Projects
Reading Club papers
Contact
|
Open Source Project Study
Candidates for Open Source Project Study
The list is not exhausted. If you take anything other
than the one in the list, please discuss with me. The purpose of this assignment
is to understand the prototype of the proposed architecture, algorithms, and
systems through running an actual prototype and present/explain to the other
people how the prototype runs, any additional work you have done including your
own applications and setup process of the prototype. This experience will give
you better understanding of the project. These Open Source Projects come with a
set of published papers and you should be able to examine your interests in the
paper through running the prototype. Some projects are rather large and may
require extensive environment and time; make sure you are able to complete this
assignment.
Suggested projects are in red colour
font.
-
Ciel
http://github.com/mrry/skywriting,
http://www.cl.cam.ac.uk/netos/ciel/
-
Apache Hadoop
http://hadoop.apache.org/
-
DryadLINQ
http://research.microsoft.com/en-us/projects/dryadlinq/
-
MapReduce Online
http://code.google.com/p/hop/
-
STREAM
http://infolab.stanford.edu/stream/
-
TelegraphCQ
http://telegraph.cs.berkeley.edu/telegraphcq/v0.2/
-
DSN
http://db.cs.berkeley.edu/dsn/
-
Naiad:
data-parallel dataflow
computation
http://research.microsoft.com/en-us/projects/naiad/, and
https://github.com/frankmcsherry/timely-dataflow (Rust version)
-
Apache Giraph: Graph processing
based on BSP
http://incubator.apache.org/giraph/
-
Spark:
Fast Cluter Computing
http://spark-project.org/
-
GPS:
A Graph Processing System
http://infolab.stanford.edu/gps/
-
GraphLab/PowerGraph:
Graph Processing
http://graphlab.org/
-
Clousera Impala:
https://github.com/cloudera/impala
-
Medusa:
http://gc.codehum.com/p/medusa-gpu/
-
Graphchi
https://github.com/GraphChi
-
X-Stream:
http://labos.epfl.ch/x-stream
-
Storm: http://storm-project.net/
-
GraphX:
https://github.com/amplab/graphx
-
DeepDive:
http://deepdive.stanford.edu/
-
Tensorflow:
https://www.tensorflow.org/
-
TensorForce:
https://github.com/reinforceio/tensorforce
-
Chaos:
https://github.com/epfl-labos/chaos
-
PyTorch:
http://pytorch.org/
-
CNTK:
https://docs.microsoft.com/en-us/cognitive-toolkit/
https://github.com/Microsoft/CNTK
-
Kubernetes:
https://kubernetes.io/docs/concepts/overview/what-is-kubernetes/
|