New Mathematics for Extreme-scale Computational Science?

Ulrich Rüde explains the underperformance of many novel algorithms and the creative research necessary to design efficient HPC software.

Riemann Mapping by Steepest Descent

In this issue’s column, Mark Levi outlines a quick constructive proof of the Riemann mapping theorem.

In this month's column, Mark Levi explains Kelvin’s theorem in two dimensions.

Mark Levi presents is a calculus-free solution of the standard vector calculus problem.

This is the first installment of a regular column by Mark Levi of the Pennsylvania State University.

The 2014 SIAM Workshop on Combinatorial Scientific Computing comprised a wide range of combinatorial topics.

The finite element method is one of the most powerful techniques for the simulation of the physical world.

Nick Higham revisits his previous review of Michael Overton's 2001 book, Numerical Computing with IEEE Floating Point Arithmetic.

As our digital footprints become more visible, and machine-to-machine communication more commonplace, cities can become “Living Labs.”

The Office of Science and Technology Policy leads inter-agency efforts to develop and implement science and technology policies and budgets.

At the SIAM Conference on Optimization last month, Dr. Retsef Levi spoke about optimizing and coordinating healthcare networks and markets.

Sam Relton discusses a recent lecture about the Raspberry Pi project and its potential use in scientific computing.

March Madness is one of the United States’ most-watched sporting events, and millions of fans compare the outcomes with their brackets.

We talk a lot about underlying methods and algorithms, but almost never talk about their incarnation: software.

Computational science fuses three distinct elements: algorithms, computer and information science, and the computing infrastructure.