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William Kahan

William Kahan 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 William Kahan rather than just read about it. In short: William "Velvel" Morton Kahan (born June 5, 1933) is a Canadian mathematician and computer scientist, who is a professor emeritus at University of California, Berkeley. He received the Turing Award in 1989 for "his fundamental contributions to numerical analysis." Biography Born to a Canadian Jewish family, he attended the University of Toronto, where he received his bachelor's degree in 1954, his master's degree in…

William Kahan — main illustration
William Kahan — illustration

Key takeaways

  • William Kahan 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 William Kahan to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of William Kahan from memory before moving on to harder problems.

Reference excerpt

William "Velvel" Morton Kahan (born June 5, 1933) is a Canadian mathematician and computer scientist, who is a professor emeritus at University of California, Berkeley. He received the Turing Award in 1989 for "his fundamental contributions to numerical analysis."

Biography Born to a Canadian Jewish family, he attended the University of Toronto, where he received his bachelor's degree in 1954, his master's degree in 1956, and his Ph.D. in 1958, all in the field of mathematics. Kahan is now emeritus professor of mathematics and of electrical engineering and computer sciences (EECS) at the University of California, Berkeley. Kahan was the primary architect behind the IEEE 754-1985 standard for floating-point computation (and its radix-independent follow-on, IEEE 854). He has been called "The Father of Floating Point", since he was instrumental in creating the original IEEE 754 specification. Kahan continued his contributions to the IEEE 754 revision that led to the current IEEE 754 standard. In the 1980s Kahan developed the program "paranoia", a benchmark that tests for a wide range of potential floating-point bugs. He also developed the Kahan summation algorithm, an important algorithm for minimizing error introduced when adding a sequence of finite-precision floating-point numbers. He coined the term "Table-maker's dilemma" for the unknown cost of correctly rounding transcendental functions to some preassigned number of digits. The Davis–Kahan–Weinberger dilation theorem is one of the landmark results in the dilation theory of Hilbert space operators and has found applications in many different areas. Kahan is an outspoken advocate of better education of the general computing population about floating-point issues and regularly denounces decisions in the design of computers and programming languages that he believes would impair good floating-point computations. When Hewlett-Packard (HP) introduced the original HP-35 pocket scientific calculator, its numerical accuracy in evaluating transcendental functions for some arguments was not optimal. HP worked extensively with Kahan to enhance the accuracy of the algorithms, which led to major improvements. This was documented at the time in the Hewlett-Packard Journal. He also contributed substantially to the design of the algorithms in the HP Voyager series and wrote part of their intermediate and advanced manuals. Kahan was named an ACM Fellow in 1994, and inducted into the National Academy of Engineering in 2005.

See also Intel 8087

References

External links William Kahan's home page An oral history of William Kahan, Revision 1.1, March, 2016 William Kahan at the Mathematics Genealogy Project A Conversation with William Kahan, Dr. Dobb's Journal , November 1, 1997 An Interview with the Old Man of Floating-Point, February 20, 1998 IEEE 754 An Interview with William Kahan April, 1998 Paranoia source code in multiple languages Paranoia for modern graphics processing units (GPUs) Archived 2016-03-03 at the Wayback Machine 754-1985 - IEEE Standard for Binary Floating-Point Arithmetic, 1985, Superseded by IEEE Std 754-2008

Illustrations

William Kahan illustration

Worked examples

Example 1 — a first encounter with William Kahan

Start with the simplest possible case. Write down what William Kahan 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 William Kahan 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 William Kahan 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 William Kahan

In research
William Kahan 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 William Kahan 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
William Kahan is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1933 births, 20th-century Canadian mathematicians, 21st-century Canadian mathematicians, so understanding it makes those chapters shorter.
In everyday life
Look for William Kahan 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 William Kahan in 20 minutes

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

Frequently asked questions

What is William Kahan in simple terms?

William "Velvel" Morton Kahan (born June 5, 1933) is a Canadian mathematician and computer scientist, who is a professor emeritus at University of California, Berkeley. He received the Turing Award in 1989 for "his fundamental contributions to numerical analysis." Biography Born to a Canadian Jewis…

Why does William Kahan 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 William Kahan?

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 William Kahan.

Tags

  • 1933 births
  • 20th-century Canadian mathematicians
  • 21st-century Canadian mathematicians
  • Canadian computer scientists
  • Canadian expatriate academics in the United States
  • Fellows of the Association for Computing Machinery
  • Jewish Canadian scientists
  • Living people
  • Numerical analysts
  • Scientific computing researchers
  • Scientists from Toronto
  • Turing Award laureates

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