Customization of floating-point units for embedded systems and field programmable gate arrays

Download files
Access & Terms of Use
open access
Copyright: Chong, Michael Yee Jern
Altmetric
Abstract
While Application Specific Instruction Set Processors (ASIPs) have allowed designers to create processors with custom instructions to target specific applications, floating-point units (FPUs) are still instantiated as non-customizable general-purpose units, which if under utilized, wastes area and performance. However, customizing FPUs manually is a complex and time-consuming process. Therefore, there is a need for an automated custom FPU generation scheme. This thesis presents a methodology for generating application-specific FPUs customized at the instruction level, with integrated datapath merging to minimize area. The methodology reduces the subset of floating-point instructions implemented to the minimum required for the application. Datapath merging is then performed on the required datapaths to minimize area. Previous datapath merging techniques failed to consider merging components of different bit-widths and thus ignore the bit-alignment problem in datapath merging. This thesis presents a novel bit-alignment solution during datapath merging. In creating the custom FPU, the subset of floating-point instructions that should be implemented in hardware has to be determined. Implementing more instructions in hardware reduces the cycle count of the application, but may lead to increased delay due to multiplexers inserted on the critical path during datapath merging. A rapid design space exploration was performed to explore the trade-offs. By performing this exploration, a designer could determine the number of instructions that should be implemented as a custom FPU and the number that should be left for software emulation, such that performance and area meets the designer's requirements. Customized FPUs were generated for different Mediabench applications and compared to a fully-featured reference FPU that implemented all floating-point operations. Reducing the floating-point instruction set reduced the FPU area by an average of 55%. Performing instruction reduction and then datapath merging reduced the FPU area by an average of 68%. Experiments showed that datapath merging without bit-alignment achieved an average area reduction of 10.1%. With bit-alignment, an average of 16.5% was achieved. Bit-alignment proved most beneficial when there was a diverse mix of different bit-widths in the datapaths. Performance of Field-Programmable Gate Arrays (FPGAs) used for floating-point applications is poor due to the complexity of floating-point arithmetic. Implementing floating-point units on FPGAs consume a large amount of resources. Therefore, there is a need for embedded FPUs in FPGAs. However, if unutilized, they waste area on the FPGA die. To overcome this issue, a novel flexible multi-mode embedded FPU for FPGAs is presented in this thesis that can be configured to perform a wide range of operations. The floating-point adder and multiplier in the embedded FPU can each be configured to perform one double-precision operation or two single-precision operations in parallel. To increase flexibility further, access to the large integer multiplier, adder and shifters in the FPU is provided. It is also capable of floating-point and integer multiply-add operations. Benchmark circuits were implemented on both a standard Xilinx Virtex-II FPGA and on the FPGA with embedded FPU blocks. The implementations on the FPGA with embedded FPUs showed mean area and delay improvements of 5.2x and 5.8x respectively for the double-precision benchmarks, and 4.4x and 4.2x for the single-precision benchmarks.
Persistent link to this record
Link to Publisher Version
Link to Open Access Version
Additional Link
Author(s)
Chong, Michael Yee Jern
Supervisor(s)
Parameswaran, Sri
Creator(s)
Editor(s)
Translator(s)
Curator(s)
Designer(s)
Arranger(s)
Composer(s)
Recordist(s)
Conference Proceedings Editor(s)
Other Contributor(s)
Corporate/Industry Contributor(s)
Publication Year
2009
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
Files
download whole.pdf 1.82 MB Adobe Portable Document Format
Related dataset(s)