Video Playback and Encoding

As we’ve covered in the past, video decode acceleration is a crucial feature for modern GPUs. The new RV770-series GPU handles advanced Blu-ray-required features, such as picture-in-picture, on the hardware, which allows for much lower CPU utilization with supported players. In our testing, CPU utilization went up about 5% when we flipped on picture-in-picture playback, while there was about a 20% increase when using an older ATI card on the same system.

Like Nvidia, ATI has demonstrated GPU-accelerated video transcodes from MPEG2 to H.264 video. While the demos run at an impressive clip, there’s no way for us to compare performance between the two cards, as neither encoder will work with both Nvidia and ATI GPUs, and neither the Element BadaBoom encoder that Nvidia uses, nor Cyberlink’s PowerDirector 7 encode using similar enough settings that we feel comfortable comparing them.

This illustrates the fundamental problem with GPU-based computing today, which we’ll talk about next.

Stream Processing

GPU-based computing promises to bring massive performance to all tasks that require massive numbers of parallel computations to occur, and the early apps, such as the Folding@Home clients, are extremely promising. However, the problem is that there’s one GPU computing API for Nvidia’s cards and a second one for ATI’s cards.

That means that anyone who writes software and wants to harness the power of GPUs needs to write not one, but two programs—one for ATI and one for Nvidia. If anything about the last 13 years of DirectX have taught us anything, it’s that in order for hardware-accelerated anything to succeed, you need to have common APIs that allow developers to write code once that works on both platforms.

We don’t know whether ATI’s Stream or Nvidia’s CUDA is the better API. Because we’re not programmers, we don’t care. But, we do know that there needs to be a common API that developers can write to that will run on every supported GPU. To make that happen, ATI and Nvidia need to put aside their differences and work together to build a common API that works on all hardware. If the two companies need a place to start, Apple pitched OpenCL, which does just that.

The Speeds and Feeds

And now, it’s time to talk about the hardware. By the time you read this, ATI will have launched both the Radeon 4850 and the Radeon 4870. Priced at $200 and $300 respectively, these cards are set to compete squarely in the mid-range.

The 4850 ships with 512MB of GDDR3 running at 993MHz on a 256-bit bus. The board we tested runs a 625MHz core and sports the same 800 stream processors as the more expensive 4870. The card will sell for between $200 and $250 depending on configuration and specs.

The Radeon 4870 is ATI’s new mid-range part, slotting it the $300 price range. The GPU core runs at 750MHz and the boards 512MB of GDDR5 memory runs at 900MHz on a 256-bit bus. Remember though, that the GDDR5 memory transfers 4 chunks of data per clock, giving it an effective memory bandwidth that’s almost double that of the 4850. For $50-$100 more, this is a Good Thing.