We believe that vector microprocessors show promise in providing high
performance at low cost for a wide range of applications. A number of
groups are evaluating the T0 vector
microprocessor and the SPERT-II
workstation accelerator board. The SPERT-II board is already in
production use speeding research in speech and image recognition.
David Johnson has
written the QuickNet program for SPERT-II, and this is in production use
training large neural networks for speech
recognition research at ICSI.
We have shipped SPERT-II boards to a number of our collaborators in
around the world
to run this and related applications.
Paola Moretto investigated the implementation of the RASTA speech
recognition front-end signal processing algorithm on
HMM Decoding Algorithms
Su-Lin Wu has
begun to look at vectorizing HMM decoding algorithms.
Krste Asanovic has
implemented Kohonen maps on T0 for a
speech coding application.
Additive Audio Synthesis
Todd Hodes is
developing an additive audio synthesis engine for
T0 based on the requirements of synthesis
systems developed at
The Center for New Music and
Audio Technologies (CNMAT).
Chris Bregler has
implemented some core image processing routines on
Fed up with waiting for his workstation to complete image convolution
Bregler has also been putting SPERT-II to
production use to speed his research in computer lipreading.
Arno Formella started to look at implementing some MPEG decompression
functions on T0.
PET is a technique that will recover the most important information in
a message no matter which packets are lost or intentionally deleted
during transmission. PET has been shown to greatly improve the
performance of MPEG transmission over the Internet. Work is underway
to port the PET algorithm to T0.
Cedric Krumbein has
ported the Berkeley MPEG Encoder to T0 and has been investigating
vectorized MPEG motion vector estimation.
Warner Warren has been writing efficient Fast Fourier Transform code
David Johnson <davidj@ICSI.Berkeley.EDU>
$Date: 2002/02/25 20:24:17 $