computer science

GraphLab

GraphLab is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand GraphLab rather than just read about it. In short: Turi is a graph-based, high performance, distributed computation framework written in C++. The GraphLab project was started by Prof.

Key takeaways

GraphLab belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect GraphLab to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of GraphLab from memory before moving on to harder problems.

Reference excerpt

Turi is a graph-based, high performance, distributed computation framework written in C++. The GraphLab project was started by Prof. Carlos Guestrin of Carnegie Mellon University in 2009. It is an open source project that uses the Apache License. While GraphLab was originally developed for machine learning tasks, it has also been developed for other data-mining tasks.

Motivation As the amounts of collected data and computing power grow (multicore, GPUs, clusters, clouds), modern datasets no longer fit into one computing node. Efficient distributed parallel algorithms for handling large-scale data are required. The GraphLab framework is a parallel programming abstraction targeted for sparse iterative graph algorithms. GraphLab provides a programming interface, allowing deployment of distributed machine learning algorithms. The main design considerations behind the design of GraphLab are:

Sparse data with local dependencies Iterative algorithms Potentially asynchronous execution

GraphLab toolkits On top of GraphLab, several implemented libraries of algorithms:

Topic modeling - contains applications like LDA, which can be used to cluster documents and extract topical representations. Graph analytics - contains applications like pagerank and triangle counting, which can be applied to general graphs to estimate community structure. Clustering - contains standard data clustering tools such as Kmeans Collaborative filtering - contains a collection of applications used to make predictions about users interests and factorize large matrices. Graphical models - contains tools for making joint predictions about collections of related random variables. Computer vision - contains a collection of tools for reasoning about images.

Turi Turi (formerly called Dato and before that GraphLab Inc.) is a company that was founded by Prof. Carlos Guestrin from University of Washington in May 2013 to continue development support of the GraphLab open source project. Dato Inc. raised a $6.75M Series A from Madrona Venture Group and New Enterprise Associates (NEA). They raised a $18.5M Series B from Vulcan Capital and Opus Capital, with participation from Madrona and NEA. On August 5, 2016, Turi was acquired by Apple Inc. for $200,000,000.

References

External links Turi homepage. SFrame: Extending GraphLab to tables

Worked examples

Example 1 — a first encounter with GraphLab

Start with the simplest possible case. Write down what GraphLab claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to GraphLab before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about GraphLab ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of GraphLab

In research: GraphLab appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses GraphLab in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: GraphLab is common in secondary-school and first-year university syllabi. It links to neighbouring topics Apple Inc. acquisitions, Data mining and machine learning software, so understanding it makes those chapters shorter.
In everyday life: Look for GraphLab outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study GraphLab in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what GraphLab means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain GraphLab out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is GraphLab in simple terms?

Turi is a graph-based, high performance, distributed computation framework written in C++. The GraphLab project was started by Prof.

Why does GraphLab matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study GraphLab?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on GraphLab.