Multi-core CPU in PhysX in action…
Multi-core CPU in PhysX in action…
Need a very fast image viewer? Just try FastPictureViewer. FastPictureViewer helps you work faster by taking advantage, when available, of the power of multicore processors and the speed of DirectX (Direct3D) graphic accelerators, all working in concert to speed up viewing experience to unprecedented levels.
FiringSquad has published an article that compares PhysX performance of CPU versus PPU versus GPU. The softwares used for this test are Unreal Tournament 3, Nurien and Warmonger.
Read the complete article here: PhysX Performance Update: GPU vs. PPU vs. CPU
In PhysX FluidMark news, I put a graph that shows CPU/PPU/GPU comparison. The results show a larger difference between PPU and GPU but this is due to the kind of test: fluid simulation.
SLI PhysX performance is also analyzed but for SLI brings so much power that the tests are CPU-bound. Anyway, SLI PhysX rocks!
More news about PhysX: PhysX News at Geeks3D.
The aim of this program is to explore the possibilities of modern 32bit CPU’s how to speed up (without any loss of precision or non-exact calculation) the traditional Mandelbrot algorithm including also full support for multiple cores. The Mandelbrot algorithm is implemented with double precision floating point numbers. You will find 3 different in the archive file:
Download Kümmel Mandelbrot Benchmark HERE.
Here are my scores on an old clock-stock Core2Duo 6600:
Do you know what CUDA and OpenCL stand for and how they could make your computer 50 times faster? If so, you can safely jump to the “Ending the mess” section below. Otherwise read on for a gentle introduction.
A computer has two important processing units: the CPU and GPU. Think of them as the two brothers in Rain Man. The GPU is the ultimate autistic savant. He’s really, really good at counting stuff and doing a lot of complex math at the same time.
The CPU is your regular guy. He can do all kinds of stuff that the savant can’t. He goes along well with everybody, as long as they speak English. If he learns to take advantage of the savant, the two of them can do amazing things like count cards at Poker.
In other words, the GPU is natural at some operations that involve repetitive calculations, like those necessary for drawing 3D graphics and doing basic image manipulation.
Read the rest of this article HERE.
Here is a small benchmark that try to compare several optimized Intel OpenCV library functions with their GPU analogs, written using OpenGL and GLSL shader language.
More information HERE.
Because I can’t resist, here is my score (Core 2 Duo 6600 default clocks, Radeon HD 3870 Catalyst8.5, WinXP 32-bit) with Resolution multiplier set to 4:
------------ CPU | GPU step1: 75.3 21.5 step2: 35.8 22.5 step3: 05.7 00.7 Total Time: 116.9 345.3
AMD will add the Havok Physics engine to both its multi-core CPUs and GPUs, but AMD managing director noted that the focus is on CPUs given feedback from gaming developers who like the idea of offsetting physics computation to CPU cores.
Read whole article HERE
AMD is hoping to accelerate Havok Physics on both its multi-core CPUs and GPUs and claims that it’s striving to deliver the best of both worlds. However, the main focus at the moment appears to be AMD’s CPUs. AMD and Havok say that they’re planning to optimise the ‘full range of Havok technologies on AMD x86 superscalar processors, and AMD claims that Havok Physics scales extremely well across the entire family of AMD processors.
Havok’s managing director, David O’Meara, explained the priority for CPUs, saying that the feedback that we consistently receive from leading game developers is that core game play simulation should be performed on CPU cores. However, he added that GPU physics acceleration could become a feature in the future, saying that ‘the capabilities of massively parallel products offer technical possibilities for computing certain types of simulation.
– AMD’s physics secret revealed: It’s Havok @ TG Daily