The Computational Science Education Reference Desk (CSERD) features resources to help students learn about computational science and to help teachers incorporate it into the classroom. Computational science involves the appropriate use of a computational architecture or computing environment (a computer, calculator, abacus, dice, or the like) to apply some algorithm, or mathematical method, to solve some scientific application, or problem. This combination of application, algorithm, and architecture results in a model that can be used as a scientific tool. The Resources section of the CSERD site provides a permanent collection of materials developed especially for CSERD, including models (pieces of scientific software), activities (lessons or lesson plans that use models), tutorials (short courses designed to teach a specific topic), applications, algorithms, architectures, and several other categories. The Resources form part of a larger catalogue of computational science items gathered by CSERD from around the internet. The catalogue can be searched or browsed by subject, keyword, education level, audience, and resource type. The record for each item includes a link to the resource, title, brief description, education level, and other information.
This java applet is a simulation that demonstrates scalar waves (such as ...
This java applet is a simulation that demonstrates scalar waves (such as sound waves) in two dimensions. It demonstrates the wave principles behind slit diffraction, zone plates, and holograms.
Hundreds of pages of Basic Math Skills. Interactive Practice on every page. ...
Hundreds of pages of Basic Math Skills. Interactive Practice on every page. An Explanation of the math topic on each page. Several Challenge Games on every page. Math Problems are randomly created.
Solves for inductor and capacitor values for first, second, third and fourth ...
Solves for inductor and capacitor values for first, second, third and fourth order passive crossover systems for two way speaker systems. Includes Butterworth, Linkwitz-Riley, Bessel, Chebychev, Legendre, Gaussian and Linear-phase type calculations.
Solve various attributes of shapes and solids. Includes calculations for circle, parallelogram, ...
Solve various attributes of shapes and solids. Includes calculations for circle, parallelogram, rectangle, square, trapezoid, right circular cone, right circular cylinder, rectangular solid, and sphere geometric formulas. Geometry attributes include volume, area, perimeter, surface area, radius, length and circumference.
Online calculator for solving various interest related equations. Includes computations for compound ...
Online calculator for solving various interest related equations. Includes computations for compound interest, simple interest, annual percentage rate(APR) and regular deposits.
The electrical relationships between resistance (R), current (I), power (P) and voltage ...
The electrical relationships between resistance (R), current (I), power (P) and voltage (E) is defined by Ohm's Law. One ohm is defined as the resistance which allow the current of one ampere under a potential difference of 1 volt.
Solve various attributes of different types of triangles. Triangle types include equilateral, ...
Solve various attributes of different types of triangles. Triangle types include equilateral, isosceles, right and scalene. Attributes include sides, angles, altitudes, medians, angle bisectors, perimeters, semiperimeters, areas, radius of circumscribed circles, Pythagorean Theorem, radius of inscribed circles.
CitcomS, a finite element code that models convection in the Earth's mantle, ...
CitcomS, a finite element code that models convection in the Earth's mantle, is used by many computational geophysicists to study the Earth's interior. In order to allow faster experiments and greater simulation capability, there is a push to increase the performance of the code to allow more computations to complete in the same amount of time. To accomplish this we leverage the massively parallel capabilities of graphics processors (GPUs), specifically those using NVIDIA's CUDA framework. We translated existing functions to run in parallel on the GPU, starting with the functions where the most computing time is spent. Running on NVIDIA Tesla GPUs, initial results show an average speedup of 1.8 that stays constant with increasing problem sizes and scales with increasing numbers of MPI processes. As more of the CitcomS code is successfully translated to CUDA, and as newer general purpose GPU frameworks like Fermi are released, we should continue to see further speedups in the future.
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