Spelling suggestions: "subject:"automatic hardware 1generation"" "subject:"automatic hardware 4egeneration""
1 |
Automatic Generation of Hardware for Custom InstructionsNecsulescu, Philip I 12 August 2011 (has links)
The Software/Hardware Implementation and Research Architecture (SHIRA) is a C to hardware toolchain developed by the Computer Architecture Research Group (CARG) of the University of Ottawa. The framework and algorithms to generate the hardware from an Intermediate Representation (IR) of the C code is needed. This dissertation presents the conceiving, design, and development of a module that generates the hardware for custom instructions identified by specialized SHIRA components without the need for any user interaction. The module is programmed in Java and takes a Data Flow Graph (DFG) as an IR for input. It then generates VHDL code that targets the Altera FPGAs. It is possible to use separate components for each operation or to set a maximum number for each component which leads to component reuse and reduces chip area use. The performance improvement of the generated code is compared to using only the processor’s standard instruction set.
|
2 |
Automatic Generation of Hardware for Custom InstructionsNecsulescu, Philip I 12 August 2011 (has links)
The Software/Hardware Implementation and Research Architecture (SHIRA) is a C to hardware toolchain developed by the Computer Architecture Research Group (CARG) of the University of Ottawa. The framework and algorithms to generate the hardware from an Intermediate Representation (IR) of the C code is needed. This dissertation presents the conceiving, design, and development of a module that generates the hardware for custom instructions identified by specialized SHIRA components without the need for any user interaction. The module is programmed in Java and takes a Data Flow Graph (DFG) as an IR for input. It then generates VHDL code that targets the Altera FPGAs. It is possible to use separate components for each operation or to set a maximum number for each component which leads to component reuse and reduces chip area use. The performance improvement of the generated code is compared to using only the processor’s standard instruction set.
|
3 |
Automatic Generation of Hardware for Custom InstructionsNecsulescu, Philip I 12 August 2011 (has links)
The Software/Hardware Implementation and Research Architecture (SHIRA) is a C to hardware toolchain developed by the Computer Architecture Research Group (CARG) of the University of Ottawa. The framework and algorithms to generate the hardware from an Intermediate Representation (IR) of the C code is needed. This dissertation presents the conceiving, design, and development of a module that generates the hardware for custom instructions identified by specialized SHIRA components without the need for any user interaction. The module is programmed in Java and takes a Data Flow Graph (DFG) as an IR for input. It then generates VHDL code that targets the Altera FPGAs. It is possible to use separate components for each operation or to set a maximum number for each component which leads to component reuse and reduces chip area use. The performance improvement of the generated code is compared to using only the processor’s standard instruction set.
|
4 |
Automatic Generation of Hardware for Custom InstructionsNecsulescu, Philip I January 2011 (has links)
The Software/Hardware Implementation and Research Architecture (SHIRA) is a C to hardware toolchain developed by the Computer Architecture Research Group (CARG) of the University of Ottawa. The framework and algorithms to generate the hardware from an Intermediate Representation (IR) of the C code is needed. This dissertation presents the conceiving, design, and development of a module that generates the hardware for custom instructions identified by specialized SHIRA components without the need for any user interaction. The module is programmed in Java and takes a Data Flow Graph (DFG) as an IR for input. It then generates VHDL code that targets the Altera FPGAs. It is possible to use separate components for each operation or to set a maximum number for each component which leads to component reuse and reduces chip area use. The performance improvement of the generated code is compared to using only the processor’s standard instruction set.
|
5 |
Generation of Application Specific Hardware Extensions for Hybrid Architectures: The Development of PIRANHA - A GCC Plugin for High-Level-SynthesisHempel, Gerald 11 November 2019 (has links)
Architectures combining a field programmable gate array (FPGA) and a general-purpose processor on a single chip became increasingly popular in recent years. On the one hand, such hybrid architectures facilitate the use of application specific hardware accelerators that improve the performance of the software on the host processor. On the other hand, it obliges system designers to handle the whole process of hardware/software co-design. The complexity of this process is still one of the main reasons, that hinders the widespread use of hybrid architectures. Thus, an automated process that aids programmers with the hardware/software partitioning and the generation of application specific accelerators is an important issue. The method presented in this thesis neither requires restrictions of the used high-level-language nor special source code annotations. Usually, this is an entry barrier for programmers without deeper understanding of the underlying hardware platform.
This thesis introduces a seamless programming flow that allows generating hardware accelerators for unrestricted, legacy C code. The implementation consists of a GCC plugin that automatically identifies application hot-spots and generates hardware accelerators accordingly. Apart from the accelerator implementation in a hardware description language, the compiler plugin provides the generation of a host processor interfaces and, if necessary, a prototypical integration with the host operating system. An evaluation with typical embedded applications shows general benefits of the approach, but also reveals limiting factors that hamper possible performance improvements.
|
Page generated in 0.1304 seconds