Next-generation, high-performance processor!

The prototype for a revolutionary new general-purpose computer processor, which has the potential of reaching trillions of calculations per second, has been designed and built by a team of computer scientists at The University of Texas at Austin.
The new processor, known as TRIPS (Tera-op, Reliable, Intelligently adaptive Processing System), could be used to accelerate industrial, consumer and scientific computing.

Professors Stephen Keckler, Doug Burger and Kathryn McKinley have been working on underlying technology that culminated in the TRIPS prototype for the past seven years. Their research team designed and built the hardware prototype chips and the software that runs on the chips.
"The TRIPS prototype is the first on a roadmap that will lead to ultra-powerful, flexible processors implemented in nanoscale technologies," said Burger, associate professor of computer sciences.
TRIPS is a demonstration of a new class of processing architectures called Explicit Data Graph Execution (EDGE). Unlike conventional architectures that process one instruction at a time, EDGE can process large blocks of information all at once and more efficiently.

Current "multicore" processing technologies increase speed by adding more processors, which individually may not be any faster than previous processors.
Adding processors shifts the burden of obtaining better performance to software programmers, who must assume the difficult task of rewriting their code to run well on a potentially large number of processors.
"EDGE technology offers an alternative approach when the race to multicore runs out of steam," said Keckler, associate professor of computer sciences.
Each TRIPS chip contains two processing cores, each of which can issue 16 operations per cycle with up to 1,024 instructions in flight simultaneously. Current high-performance processors are typically designed to sustain a maximum execution rate of four operations per cycle.
Though the prototype contains two 16-wide processors per chip, the research team aims to scale this up with further development.