We describe a novel approach for automatically generating streaming architectures from software programs. While existing systems require user-defined stream models, our method automatically identifies producer-consumer streaming relationships and translates them into streaming architectures. Data streams between producer-consumer kernels are represented using a combination of stream descriptors and CFGs, which are categorized into four stream types. A bridge module is generated based on the stream type in the streaming architecture to facilitate data streaming between each producer-consumer pair. Several optimizations are also developed to improve throughput and parallelism. We demonstrate our results on a FPGA based platform. The automatically generated streaming architectures show 1.5-3x speedups over the non-streaming designs by employing spatial and temporal data independence to increase parallelism.

This paper describes an FPGA based implementation of a real time compression algorithm used in transactions between financial institutions such as exchanges and trading houses. FIX is a protocol that has gained widespread popularity for exchanging financial information such as stock prices and purchases over the Internet. If a financial trader can speed up the processing of these protocols, he can make significant financial profits by buying or selling stocks when there is a lot of variability in the share prices. Our methodology tries to recognize and exploit streaming characteristics of the software design in order to implement a pipelined parallel processing system in reconfigurable hardware. It introduces the concept of caches to keep stream pipelines filled more often. The system implemented on a Xilinx Virtex5 LX110T FPGA shows a 17x speedup in throughput over a software implementation running on a dual core Intel Pentium workstation. These techniques are being developed as part of commercial compiler project to automatically translate software binaries to streaming RTL VHDL systems.

With the proliferation of reconfigurable systems and flexible memory architectures, there has been intense interest in stream systems. While the existing stream systems require the programs to be written using special models, this paper demonstrates an approach to automatically generate stream programs from existing applications written for non-stream scalar processors. As a part of this approach, we provide a new comparison methodology and an algorithm to automatically generate stream descriptions. A second algorithm identifies processing kernels that can be pipelined. We demonstrate our results on an FPGA based platform.

Many new real-time system require high-speed compression and decompression solutions that provide low latency links between systems over a network interface. We describe a methodology for implementing an optimized streaming ZLIB decoder system on a Xilinx Virtex-5 FPGA board, which exploits the fine-grain parallelism in the software architecture to improve the performance. We describe a ZLIB decoder system in hardware and concrete examples of how to transform the sequential software algorithm into a highly optimized hardware implementation in RTL VHDL. Experimental results show 50times speedup in terms of cycles and 2.83times speedup in terms of time in the FPGA over the software. The ZLIB decoder was shown to operate at a rate of 1 GBit/s.

As new applications in embedded communications and control systems push the computational limits of digital signal processing (DSP) functions, there will be an increasing need for software applications to be migrated to hardware in the form of a hardware-software codesign system. In many cases, access to the high-level source code may not be available. It is thus desirable to have a technology to translate the software binaries intended for processors to hardware implementations. This paper provides details on the retargetable FREEDOM compiler. The compiler automatically translates DSP software binaries to register-transfer level (RTL) VHDL and Verilog for implementation on field-programmable gate arrays (FPGAs) as standalone or system-on-chip implementations. We describe the underlying optimizations and some novel algorithms for alias analysis, data dependency analysis, memory optimizations, procedure call recovery, and back-end code scheduling. Experimental results on resource usage and performance are shown for several program binaries intended for the Texas Instruments C 6211 DSP (VLIW) and the ARM 922 T reduced instruction set computer (RISC) processors. Implementation results for four kernels from the Simulink demo library and others from commonly used DSP applications, such as MPEG-4, Viterbi, and JPEG are also discussed. The compiler generated RTL code is mapped to Xilinx Virtex II and Altera Stratix FPGAs. We record overall performance gains of 1.5-26.9 for the hardware implementations of the kernels. Comparisons with the power aware compiler techniques (PACT) high-level synthesis compiler are used to show that software binaries can be used as intermediate representations from any high-level language and generate efficient hardware implementations.

This paper describes a method for automatically extracting function bodies from linked software binaries. It utilizes procedure-calling conventions along with limited control and data flow information. It has been tested with the TI C6000 DSP processor platform. Results are reported on eight benchmarks for which our algorithm successfully identifies all functions. It identifies 198% more functions than by the use procedure calling conventions alone.

The introduction of advanced FPGA architectures, with built-in DSP support, has given DSP designers a new hardware alternative. By exploiting its inherent parallelism, it is expected that FPGAs can outperform DSP processors. This paper describes the process and considerations for automatically translating binaries targeted for general DSP processors into Register Transfer Level (RTL) VHDL or Verilog code to be mapped onto commercial FPGAs. The Texas Instruments C6000 DSP processor architecture is chosen as the DSP processor platform, and the Xilinx Virtex II as a target FPGA. Various optimizations are discussed, including data dependency analysis, procedure extraction, induction variable analysis, memory optimizations, and scheduling. Experimental results on resource usage and performance are shown for ten software binary benchmarks. Results show performance gains of 3-20X in the FPGA designs over that of the DSP processors in terms of reductions of execution cycles.

Applications that require digital signal processing (DSP) functions are typically mapped onto general purpose DSP processors. With the introduction of advanced FPGA architectures with built-in DSP support, a new hardware alternative is available for DSP designers. By exploiting its inherent parallelism, it is expected that FPGAs can outperform DSP processors. However, the migration of assembly code to hardware is typically a very arduous process. This paper describes the process and considerations for automatically translating software assembly and binary codes targeted for general DSP processors into register transfer level (RTL) VHDL or Verilog code to be mapped onto commercial FPGAs. The Texas instruments C6000 DSP processor architecture has been used as the DSP processor platform, and the Xilinx Virtex II as the target FPGA. Various optimizations are discussed, including loop unrolling, induction variable analysis, memory and register optimizations, scheduling and resource binding. Experimental results on resource usage and performance are shown for ten software binary benchmarks in the signal processing and image processing domains. Results show performance gains of 3-20x in terms of reductions in execution cycles and 1.3-5x in terms of reductions in execution times for the FPGA designs over that of the DSP processors in terms of reductions in execution cycles.

Migration of software from older general purpose embedded processors onto newer mixed hardware/software Systems-On-Chip (SOC) platforms is becoming an increasingly important topic. Automatic translation of general purpose software binaries and assembly code onto hardware implementations using FPGAs require sophisticated scheduling and allocation algorithms to maximize the resource utilization of such hardware devices. This paper describes the effects of scheduling and chaining of node operations in a CDFG onto an FPGA. The effects of register allocation on scheduled nodes are also discussed. The Texas Instruments C6000 DSP processor architecture was chosen as the DSP processor platform and assembly code, and the Xilinx Virtex II XC2V250 was chosen as the target FPGA. Results are reported on ten benchmarks, which show that scheduling with chaining operations produces the best results on FPGAs, while the addition of register allocation in fact generates poorer designs in terms of area and frequency.

This paper describes a behavioral synthesis tool called AccelFPGA which reads in high-level descriptions of digital signal processing (DSP) applications written in MATLAB, and automatically generates synthesizable register transfer level (RTL) models and simulation testbenches in VHDL or Verilog. The RTL models can be synthesized using commercial logic synthesis tools and place and route tools onto field-programmable gate arrays (FPGAs). This paper describes how powerful directives are used to provide high-level architectural tradeoffs for the DSP designer. Experimental results are reported on a set of eight MATLAB benchmarks that are mapped onto the Xilinx Virtex II and Altera Stratix FPGAs.

Recently, high-level languages such as MATLAB have become popular in prototyping algorithms in domains such as signal and image processing. Many of these applications whose subtasks have diverse execution requirements, often employ distributed, heterogeneous, reconfigurable systems. These systems consist of an interconnected set of heterogeneous processing resources that provide a variety of architectural capabilities. The objective of the MATCH (MATLAB Compiler for Heterogeneous Computing Systems) compiler project at Northwestern University is to make it easier for the users to develop efficient code for distributed heterogeneous, reconfigurable computing systems. Towards this end we are implementing and evaluating an experimental prototype of a software system that will take MATLAB descriptions of various applications, and automatically map them on to a distributed computing environment consisting of embedded processors, digital signal processors and field-programmable gale arrays built from commercial off-the-shelf components. We provide an overview of the MATCH compiler and discuss the testbed which is being used to demonstrate our ideas. We present preliminary experimental results on some benchmark MATLAB programs with the use of the MATCH compiler.