This
DARPA-sponsored
research project seeks to develop a complete
adaptive computing solution for general-purpose computation. It
includes efforts on adaptive computer architectures, configuration
management, high-level compilation, template-based physical design,
and military applications of adaptive computing technology.
Adaptive Computing Architectures
In order to demonstrate the advantages of single-chip integration of
reconfigurable logic with a host processor, as well as the speculative
execution model proposed, we will develop the
Chimaera hardware system.
We will develop a VLSI implementation of the
Chimaera Reconfigurable Logic Array,
and demonstrate the achievable performance
of this array. We will also investigate high-performance carry
chains, and create VLSI implementations of our proposed logic
structures. Finally, we will create the architecture for the rest of
the system, and demonstrate the complete system architecture operating
on complex applications.
Configuration Management for Adaptive Computing
We have proposed numerous techniques for configuration management for
adaptive computing. New techniques proposed here include
high-performance configuration buses and configuration compression and
decompression algorithms. We will develop a high-performance bus
structure optimized for carrying configuration data for adaptive
computers, leveraging current techniques in high-performance
sequential memory bus structures. We will also create compression
algorithms appropriate for adaptive computing, allowing configuration
size to be reduced while allowing for efficient decompression during
reconfiguration. To demonstrate these techniques we will develop a
VLSI implementation of the decompression algorithms for inclusion in
our adaptive computing system.
Eliminating reconfiguration overhead requires more than just
compression and fast bus structures. To remove this bottleneck we
will develop an integrated configuration management system. This
system will include the high-performance configuration bus and
compression algorithms described earlier, as well as the integration
of prefetching, configuration caching, multi-level caching, dynamic
contexts, and partial run-time reconfiguration. We will develop a
prototype system including all of these optimizations, and demonstrate
their performance on the applications investigated in this proposal.
High-level Compilation for Adaptive Computing
Adaptive computing systems require not just efficient hardware, but
also software sophisticated enough to achieve high-performance
implementations of user algorithms. To achieve this goal we will
develop high-level compilation support to translate source programs in
a high-level language into assembly language and reconfigurable logic
implementations for adaptive computers. These tools will create
implementations automatically in approximately the same time as a
standard software compiler.
Our compiler for adaptive computers will include several advanced
optimizations. In order to reduce the complexity of the logic mapped
to the reconfigurable logic, and create the fastest implementation, we
will apply strength reduction transformations to replace difficult to
implement instructions with simpler alternatives. To increase the
benefit of an RFUOP, we will develop techniques (similar to cache
blocking) which can group operations together that can take advantage
of the same RFUOP. Parallelism in the code will also be considered,
and we will extract parallelism from the program to allow
multi-threaded operation which can help hide reconfiguration latency.
We will also develop code motion techniques, which can increase the
regions of the code that can be mapped to reconfigurable logic.
Finally, we will investigate support for variable-precision
arithmetic, and create compiler optimizations that can automatically
take advantage of this unique opportunity in reconfigurable logic.
Each of these optimizations will be implemented in software, and
merged into a complete compiler for adaptive computers.
Template Based Physical Design
Once the high-level compiler has transformed a program into assembly
language, with some regions of the code identified for migration to
reconfigurable logic, it is necessary to create an implementation of
these code regions. In order to provide high quality implementations,
while maintaining compile times similar to standard software
compilers, we are developing a template-based compilation methodology.
We will develop algorithms to take regions of assembly language and
replace them with logic templates, and then floorplan the
reconfigurable logic. This will create an initial layout for the
circuit. Then, we will investigate techniques for merging connected
templates and remove extraneous logic elements. From there, we will
develop template-based placement and routing tools, physical design
algorithms optimized to take advantage of the structure of the
templates while allowing enough flexibility to create high-quality
implementations. We will develop each of these algorithms, and create
a complete back-end compiler for the reconfigurable logic in an
adaptive computer system. Once this system is operational, we will
investigate methods for run-time constant propagation, which will
reoptimize a configuration to take advantage of knowledge about
parameters only obtainable at runtime.
Military Applications for Adaptive Computing
In order to demonstrate our techniques, and guide the development of
the hardware and software constructs contained in this proposal, we
will develop implementations of important classes of military-relevant
algorithms on adaptive computers. These applications will include
Automatic Target Recognition, Data Encryption and Compression, Image
and Signal Processing, Variable Precision Arithmetic, Emulation of
Legacy Computing Systems, and BDD-based VLSI/CAD algorithms. These
implementations will include both hand-optimized, automatically
generated, and library-based solutions.