Supercomputer On-a-Chip Prototype Unveiled

An anonymous reader writes "Researchers at University of Maryland have developed a prototype of what may be the next generation of personal computers. The new technology is based on parallel processing on a single chip and is 'capable of computing speeds up to 100 times faster than current desktops.' The prototype 'uses rich algorithmic theory to address the practical problem of building an easy-to-program multicore computer.' Readers can win $500 in cash and write their names in the history of computer science by naming the new technology."

Comments

Human-guided autovectorization.

[Ayanami Rei]

You know, autovectorization looks good on paper. But for most tasks, it really doesn't net you any benefit unless you can separate all your work into non-overlapping chunks. You can't have any interdependancies on your working set (or risk expensive, non-scalable locking), and if you're all pulling from a single data source to split up the analysis work you'll spend a lot of time in contention for the pipe to that resource.

For example, it wouldn't make searching a database (scratch that, searching any data set) any faster unless the index was already pre-split among the processing units.

In this architecture the processing units have the same bus to RAM and disk on the front and back ends and have to deal with contention.

Your system is only as fast as the slowest serial part. Typically this is storage media, a network connection, or a memory crossbar. Processors really are fast enough for the non-embarrasingly parallel stuff. They are at the right ratio with respect to the other slower busses to do most general purpose work.

If you want to do more than that then its other things; storage media, memory, I/O busses -- that need to be multiplied in density and number. Only then can we see higher throughput.

Autovectorization is only good for things we already have offloading for anyway (TCP encryption, graphics, sound)... and for those general purpose cases like in Game AI where you might want a linear algebra boost NVidia has beaten these guys to the punch with the GP stream processing in the newest chips and the very flexible Cg language/environment.