Monte Carlo uses a statistical computing method for solving complex scientific computing problems. It innovatively uses random numbers to simulate the uncertainty of inputs to a problem and processes the repeated sampling of the parameter to obtain a deterministic result and solve problems that would otherwise be impossible. This method was originally pioneered by nuclear physicists involved in the Manhattan Project in late 1940s. It is named after the biggest casino in the principality of Monaco.
By Shwetha Doss, Sr. Application Engineer, Intel Corporation
Chethan Raj, Developer, CodeCraft Technologies/Focus Medica
Perceptual computing is reshaping the way we interact with our devices, making it more natural, intuitive, and immersive. Devices will be able to perceive our actions through hand gestures, finger articulation, speech recognition, face tracking, augmented reality, and more. To support perceptual computing, Intel introduced the Intel® Perceptual Computing SDK, a library for pattern detection and recognition algorithms.
I’ll try to figure out what is new for Intel® Atom™ architecture in new versions of GCC and how this affects performance and code size on the well-known EEMBC® CoreMark® benchmark: www.coremark.org
The chart below shows CoreMark performance results for base and peak option sets on various GCC versions relative to GCC 4.4.6 base performance (higher is better):