Overview

The Integrating Information, Science, and Technology for Prediction (IS&T) pillar addresses:

• emerging challenges in national security,
• societal prosperity,
• and fundamental science.

The IS&T pillar leverages advances in theory, algorithms, and the exponential growth of high-performance computing to accelerate the integrative and predictive capability of the scientific method.

IS&T pillar strategy

The IS&T pillar will focus on the integration of Lab assets for understanding, quantified prediction, and design of complex natural and engineered systems.

As we continue to integrate discovery science, validated theory, computational algorithms, software infrastructure, and computing hardware, this “toolset” becomes particularly suited to the advanced computing architectures of the future, which will likely be increasingly heterogeneous and multicore and will be designed for both compute-intensive and data-intensive applications.

Emerging challenges

The new millennium presents us with a number of emerging challenges such as energy security, climate change, international terrorism, the aging of our nuclear deterrent, and the proliferation of nuclear weapons. These global challenges are notable for their daunting scale as well as their extreme level of complexity.

Our significant national assets in observational and experimental data acquisition, computational capacity, and modeling and simulation are already addressing these challenges.

These emerging application frontiers are revolutionary in their requirements. As a result, we need to exercise the scientific method at a scale of complexity that is only now becoming feasible.

Los Alamos areas of leadership in IS&T

Strong capabilities are being developed in three common, cross-cutting IS&T areas:

• Complex Networks. Description of complex systems by their interdependent subsystems and components: cyber systems, national infrastructure, biological systems, social networks, terrorist networks, smart grid, etc.
• Computational Co-Design. Design of interacting components of a computational system as a whole, producing significantly better, perhaps even revolutionary, design.
• Data Science at Scale. Extremely large datasets and extremely high-rate data streams in cybersecurity, energy security, climate modeling, astrophysics, biology, etc.

Historical roots of the IS&T pillar

Modern computational science (e.g. Monte Carlo) has its roots in the Manhattan Project at Los Alamos National Laboratory with renowned scientists such as Fermi, Ulam, von Neumann, and Metropolis. 

Monte Carlo research, methods development, and applications on the world's most powerful computers, for the nation’s most urgent needs remain a forte of Los Alamos, particularly in the mission areas of nuclear deterrence, global threats, and energy security.