mathematics

Laura Grigori

Laura Grigori is a mathematics 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 Laura Grigori rather than just read about it. In short: Laura Grigori is a French-Romanian applied mathematician and computer scientist known for her research on numerical linear algebra and communication-avoiding algorithms. She is a director of research for the French Institute for Research in Computer Science and Automation (INRIA) in Paris, and heads the "Alpines" scientific computing project jointly affiliated with INRIA and the Laboratoire Jacques-Louis Lions of So…

Key takeaways

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

Reference excerpt

Laura Grigori is a French-Romanian applied mathematician and computer scientist known for her research on numerical linear algebra and communication-avoiding algorithms. She is a director of research for the French Institute for Research in Computer Science and Automation (INRIA) in Paris, and heads the "Alpines" scientific computing project jointly affiliated with INRIA and the Laboratoire Jacques-Louis Lions of Sorbonne University.

Education and career Grigori earned her Ph.D. from Henri Poincaré University in 2001. Her dissertation, Prédiction de structure et algorithmique parallèle pour la factorisation LU des matrices creuses, concerned parallel algorithms for LU decomposition of sparse matrices, and was supervised by Michel Cosnard. After postdoctoral research at the University of California, Berkeley and the Lawrence Berkeley National Laboratory, she became a researcher for INRIA in 2004, and became the head of the Alpines project in 2013. In 2021, she will join the SIAM Council as a Member-at-Large.

Recognition A 2012 paper on communication-avoiding algorithms for parallel matrix decomposition by Grigori with James Demmel, Mark Hoemmen, and Julien Langou won the 2016 Society for Industrial and Applied Mathematics (SIAM) Activity Group on Supercomputing Best Paper Prize for the best paper on parallel scientific and engineering computing from the previous four years. Grigori has been an invited plenary speaker at many international conferences on scientific computing. In 2020 Grigori was named a SIAM Fellow "for contributions to numerical linear algebra, including communication-avoiding algorithms".

References

External links Laura Grigori publications indexed by Google Scholar

Worked examples

Example 1 — a first encounter with Laura Grigori

Start with the simplest possible case. Write down what Laura Grigori claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, 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 Laura Grigori 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 Laura Grigori 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 Laura Grigori

In research: Laura Grigori appears in mathematics 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 Laura Grigori 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: Laura Grigori is common in secondary-school and first-year university syllabi. It links to neighbouring topics Fellows of the Society for Industrial and Applied Mathematics, French mathematicians, French women mathematicians, so understanding it makes those chapters shorter.
In everyday life: Look for Laura Grigori 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 Laura Grigori in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Laura Grigori 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 Laura Grigori out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Laura Grigori in simple terms?

Why does Laura Grigori matter?

Because it connects several mathematics 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 Laura Grigori?

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 Laura Grigori.