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NVIDIA Tesla 870 finds application in medicine, dramatically accelerating ultrasound scanner

A small company TechniScan, which began developing ultrasound scanners in the late 90s
years, has developed a new progressive device – UltraSoundCT. This product
relies on the power provided by GPUs and will serve
medical purposes.

UltraSoundCT uses ultrasound to scan the breast. This
the approach, as the source notes, is more a more comfortable procedure than
mammogram. However, for doctors, it creates some inconvenience in terms of
speed of obtaining scan results. The developers of such scanners
type immediately drew attention to what power was required for rendering
(“Rendering”) the image.

The 12-node cluster built by TechniScan five years ago was based on processors
Pentium M and getting doctors of the finished picture on such a system took 118 minutes. More
cheap, 6-node system, worked even longer (albeit not much) – 135
minutes, which made it clear to the researchers that general-purpose processors are not
the best choice. Using the later CPUs
Pentium 4, Core 2 Duo and even Core 2
Quad confirmed this conclusion, because due to the 16-core cluster on the Core 2 to reduce the time
waiting only up to 45 minutes.

The problem was solved by the programmer of the company Jim Hardwick (Jim Hardwick),
used the GeForce 8-series cards and the development kit (SDK) of the company
NVIDIA for CUDA (Complete Unified Device Architecture). Ported to CUDA code
turned out to be working, and the GPU approach is
more than successful. Subsequently, boards were used
Tesla C870,
released by NVIDIA just a year ago.

According to TechniScan, doctors now expect
the appearance of the picture is only 15-20 minutes before they can be diagnosed and
write the required prescription.
This is due to the fact that the GeForce 8800
GTX is at least 8 times faster than Core 2 Quad processor (2.66 GHz) at
rendering an image. Accordingly, 4 such GPUs
were able to significantly speed up the process of image processing.

Besides the speed that
importantly, the GPU-based system will also benefit from
TCO (cost of ownership), which is $ 15
000 – $ 20,000, while traditional
clusters on the CPU cost about
$ 1,000,000.

TechniScan specialists are now
pending what new product will be released in the line
Tesla. Perhaps the next generation of accelerator boards will allow them
scanner, UltraSoundCT, within 10 minutes to process the image. In the present
the scanner is already undergoing clinical trials and within two years
will appear on the market.


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