The CPU redefined: AMD Torrenza and Intel CSI

Introduction

AMD buys out ATI, Intel and Nvidia seem to form a strategic alliance; in short these are turbulent times in the world of chip manufacturers. If we are to believe the statements made by several manufacturers, then we are on the threshold of some major changes concerning task applications for the various chips in a PC. Though AMD has gotten a head start with Torrenza, Intel won't be far behind in implementing a similar solution.

Gone are the days when the CPU was the only central powerhouse of a computer. The first example that springs to mind is the GPU, the cetral chip on the video card: modern 3D chips are completely programmable and offer an almost unbelievable amount of raw processing power, but it doesn't stop there. Other examples are Creative's X-Fi chip, which has been implemented in its latest soundcards, which is so powerful that by right it can actually be called an APU (Audio Processing Unit) and Ageia's PPU's (Physics Processing Units). These PPU's are used dedicated to processing the physics calculations within games. Another company to appear on the news a short while ago was AISeek. This company made tech related headlines with the announcement that it was developing a processor dedicated to handling the Artificial Intelligence calculations within 3D games. Another prime example is the professional world where there are numerous chips capable of handling various calculations very efficiently hence decreasing the workload for the CPU.

Co-processors

All the afore mentioned examples show that specialised chips for specific tasks can be quite a smart move under certain circumstances. Take for example processors such as the AMD Athlon 64 or the Intel Core 2 Duo; these have to be capable of processing almost any form of code. The downside of this is that they aren't optimised for a specific task, hence their basically jack's of all trades but masters of none. Taking this into account it should come as no surprise that a modern 3D-chip is capable of creating beautiful images a hundred times faster than any CPU. The same counts for any of the aforementioned examples.

In the past the processor was the beating heart of the computer (hence the term Central Processing Unit) but with all the different developments in abovementioned areas the CPU is becoming a less determining factor for overall processing power within the PC. Modern GPU's have already taken over many of the tasks that CPU's did in the past and as time goes by we will see more and more of these specialised chips. Several people within the IT-industry predict that in the near future we will see more specialised co-processors appearing on the market, for any form of task. If you mainly use your PC for video editing, then wouldn't be more efficient to have a specialised co-processor capable of handling the required calculations far more efficiently than a standard CPU? Or when a PC is used for certain scientific calculations, wouldn't it be far handier to have a co-processor which had been specialised for that certain area?

With al the GPU's, APU's, PPU's and AIPU's we can definitely say that the Personal Computer has become more powerful and diverse than ever before, but the flipside of this is that we have to look critically at how we implement these various innovations within a PC: using only the PCI- and PCI-Express-bus for expansion cards with specialised processors is not exactly efficient by any means....

Stream computing

In terms of co-processors it's quite interesting to see what ATI has been up to lately. In the last couple of years GPU's have developed from relatively simple chips, capable of handling only a few standard processes, to veritable processing behemoths. GPU's became fully programmable with the advent of DirectX 8 and are even capable of working with 32-bit floating point numbers since DirectX 9, this has led to more and more companies using GPU's for far more than just calculating 3D images. The most notable step forward has been the recent announcement by both ATI and nVidia to implement their GPU's as PPU's to handle physics calculations in 3D-games, this as a reaction to the PPU-chip from Ageia. ATI has taken this one step further in announcing a far wider scope of possible uses for their GPU's: ATI, under the codename Stream computing, is proactively supporting the implementation of their GPU's for a myriad of calculation processes.

During a recent presentation ATI emphasized that a GPU is far more suitable for working through various calculations than a traditional CPU. According to ATI the latest generation video cards is up to 16 times faster at financial risk calculations than a modern processor, 20 times faster at granular studies and even up to 40 times faster at Folding@home operations used by Stanford University to do research on diseases.

ATI have released a beta-version of the Folding@home client as a proof-of-concept, which you can use with any video card from the X1900 family. Though the software doesn't offer any benchmarking possibilities, it is quite clear from our own tests that the Radeon chips are far efficient at processing the calculations required for Folding@home then processors from either AMD or Intel. It can be safe to say that this was partially developed to coincide with the new Torrenza-platform developed by AMD, ATI's new owner.