2004-05-10, 16:22
so best would probably be to code/write a dedicated and extremely xbox optimized non-mplayer based core for mpeg-2/ts playback?
Quote:audio supercomputer hidden in your graphics card?too bad they didn't decide to make it open source huh? :tear: well, maybe someone will find a way to reverse-engineer or replicate it
by wolfgang gruener, senior editor
september 2, 2004 - 13:59 est
cambridge (ma) - nvidia's graphic cards may have much more to offer than simply drawing pixels on the screen: a startup company has found a way to translate audio signals into graphics, run them through the graphics card and overcome a common issue of limited audio effect processing performance in computers.
it is not unusual that professional music artists run into performance barriers even with the most powerful computers today. multi-track recording still is a challenging and sometimes frustrating task. james cann from bionicfx in massachusetts however noticed that audio processing task does not have to happen just in the cpu. his audio video exchange technology (avex) converts digital audio in graphics data and then performs effect calculations using the 3d architecture of nvidia gpus. compared to the capability of just six gflops of a typical cpu, nvidia's chips can reach more than 40 gflops, according to cann.
"this technology allows music hobbyists and professional artists to run studio quality audio effects at high sample rates on their desktop computer," he said. cann's invention is purely software-based and is not capable substituting a sound chip. the approach exploits the video card 3d chip, which usually is idle when users are working with multi-track recording software. "it's a great resource to use as a coprocessor," cann said. "avex is designed to reduce the cpu load by moving the processing to the video card for certain types of audio effects when making music." cann said that the technology is purely targeted at music enthusiasts and at this time brings no advantages for applications such as gaming.
but if cann is right, audio effect processing might be just a starting point how a gpu could be used for other applications. he believes that several other software types could be greatly enhanced in the same way, such as genomics or seti. "the gpu has some numeric precision issues that need to be worked out for scientific applications to be possible, but the thought of performing the computations on a resource theoretically capable of 50 and more gflops of the gpu instead of five gflops of the cpu is exciting," he said.
so far cann cannot take as much performance away from the gpu as he would like. "right now, getting the data back from the video card is very slow, so the overall performance isn't even close to the theoretical max of the card. i am hoping that the pci express architecture will resolve this. this will mean more instances of effects running at higher sample rates," he said.
still, there is significant boost of performance and reduce the load for cpu for people who are using applications such as cubase, ableton live, and other vst compatible hosts. cann's first commercial application will be bionicreverb, which is expected to go into public and free beta in october. the final version is scheduled to be released at the winter namm conference in january 2005.
bionicreverb is an impulse response reverberation effect that runs as a plug-in inside vst compatible multi-track recording software. the audio effect is generated by combining an impulse response file with digital audio. impulse response files are created by firing a starter pistol inside a location, such as carnegie hall, and recording the echoing sound waves. combining the two files through mathematical convolution is a cpu intensive process that is reduced by moving expensive calculations onto the gpu. amateur and professional guitarists, singers, pianists, and other musicians will be able to create performances in their home or studio that sound exactly like they were recorded in famous locations around the world, according to cann.
at this time, cann plans to only support nvidia graphics cards. "when i started, ati had a problem with floating point data. i have heard they have resolved it, but i won't have time to purchase and research their newest cards until after this is released," he said.
pricing was not announced yet, but cann says he will make his technology available for "far less" than the cost of professional studio dsp solutions which can run into the high five-figure range. he estimates the price will be somewhere between $200-$800.
Quote:graphics processors supercharge everyday appsa good dedicated site on the subject is; gpgpu (link), the general-purpose computation using graphics hardware site, (quote: "with the increasing programmability of commodity graphics processing units (gpus), these chips are capable of performing more than the specific graphics computations for which they were designed. they are now capable coprocessors, and their high speed makes them useful for a variety of applications. the goal of this page is to catalog the current and historical use of gpus for general-purpose computation.")
by scott fulton
june 30, 2005 - 16:13 est
chapel hill (nc) - originally developed to remove a massive processing workload from the cpu, some scientists examine how the graphics processors can accelerate non-graphic applications as well. the geometric algorithms for modeling, motion, and animation (gamma) research group at the university of north carolina at chapel hill, reported this week that nvidia's 7800 gtx reference card increased the speed of test applications by up to 35x.
researchers with gamma said they found enormous performance capabilities in nvidia's newest graphics card that substantially outpaces its predecessor, the geforce 6800 ultra. compared to the 6800, the 7800 tripled performance; without the help of a graphics chip, the speed gains were between 8x and up to 35x. the discovery points to the removal of a bandwidth bottleneck, which may lead to the unimpeded development of co-processing libraries and software development kits (sdks) for everyday applications, such as spreadsheets and database management systems.
"it seems to me that the floating-point bandwidth on the new hardware is much more than on a 6800 ultra," reported naga k. govindaraju, research assistant professor at unc's department of computer science, in an interview with tom's hardware guide. "on a 6800 ultra, we are, in some manners, very limited...since the bandwidth is not good enough on the card, we were still not able to use the full performance of the card. on a 7800 gtx, it seems to me that the floating-point bandwidth is much higher."
the trick to exploiting the latent power of the graphics processor while it isn't producing scenery for 3d games, unc professor dinesh manocha told us, is to rephrase everyday operations as though they were specific two-dimensional graphics functions, like texture mapping. while everyday cpus work with threads, prof. minocha pointed out, graphics processors deal with streams capable of performing single instructions on multiple data elements simultaneously, through pipelines. by comparison, cpu-based parallelism divides instruction threads among multiple cores, for what prof. minocha calls a "von neumann bottleneck." the nvidia 7800 gtx utilizes 24 pixel pipelines and eight vertex units for its implementation of single instruction / multiple data (simd) architecture.
this technique of essentially pretending everything is a game, stated prof. govindaraju, reduces the critical elements of such everyday functions as sorting algorithms to a single instruction, which the graphics processor then applies to multiple pipelines at once. recent test results presented by the gamma team compared the performance of their gpusort algorithm to a traditional linear quicksort algorithm, compiled first under microsoft visual c++, then under intel's c++, which is optimized for hyperthreading. for sorting an array of 18 million elements, the visual c++ routine required about 21 seconds to accomplish what the gpusort routine produced in under 2. hyperthreading and the intel compiler boosted quicksort performance to about 17 seconds.
one of the purposes of the gamma team's work is to demonstrate the extent to which computing power in everyday pcs lies dormant, especially with regard to mere productivity applications as opposed to computation-rich 3d games. profs. manocha and govindaraju agree that general purpose computation libraries for such programs as excel and matlab could be the first step to the future development of sdks that make full-time use of graphics chips as math coprocessors.
but what prof. manocha also pointed out is that the performance increase in gpus is exceeding the rate of cpus. "if you look at [both] computation power and rasterization power," stated prof. manocha, "in the last six years, [performance for] pc graphics cards has grown at a [factor] of 2 or 2.25 per year, whereas cpus are barely doubling every 18 months." he added that he expects this trend to continue as both ati and nvidia produce their next generations of graphics cards in 2006.