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A BFG Physx card. PhysX is an open-source [1] realtime physics engine middleware SDK developed by Nvidia as part of the Nvidia GameWorks software suite.. Initially, video games supporting PhysX were meant to be accelerated by PhysX PPU (expansion cards designed by Ageia).
PhysX: For physics, destruction, particle and fluid simulations. OptiX: For baked lighting and general-purpose ray-tracing. Core SDK: For facilitating development on Nvidia hardware. In addition, the suite contains sample code for DirectX and OpenGL developers, as well as tools for debugging, profiling, optimization, and Android development.
Ageia, founded in 2002, was a fabless semiconductor company.In 2004, Ageia acquired NovodeX, the company who created PhysX – a Physics Processing Unit chip capable of performing game physics calculations much faster than general purpose CPUs; they also licensed out the PhysX SDK (formerly NovodeX SDK), a large physics middleware library for game production.
The term was coined by Ageia's marketing to describe their PhysX chip to consumers. Several other technologies in the CPU-GPU spectrum have some features in common with it, although Ageia's solution was the only complete one designed, marketed, supported, and placed within a system exclusively as a PPU.
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When the download finished the install wizard will show up. Click Yes. Click Install. After the installation you will be asked for your email address for activation. Enter the email address used for purchasing System Mechanic. Click Begin Activation and follow the on screen instructions to finish setting up System Mechanic.
Bullet is a physics engine which simulates collision detection as well as soft and rigid body dynamics.It has been used in video games and for visual effects in movies. Erwin Coumans, its main author, won a Scientific and Technical Academy Award [4] for his work on Bullet.
In computing, CUDA (Compute Unified Device Architecture) is a proprietary [2] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.