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Architecture description languages (ADL) have been established to aid the design of application-specific instruction-set processors (ASIP). Their main contribution is the automatic generation of a software toolkit, including C compiler, assembler, linker, and instruction-set simulator. Hence, the challenge in the design of such ADLs is to unambiguously capture the architectural information required for the toolkit generation in a single model. This is particularly difficult for C compiler and simulator, as both require information about the instructions' semantics, however, while the C compiler needs to know what an instructions does, the simulator needs to know how. Existing ADLs solve this problem by either introducing redundancy or by limiting the language's flexibility. This paper presents a novel, mixed-level approach for ADLbased instruction-set description, which offers maximum flexibility while preventing from inconsistencies. Moreover, it enables capturing instruction-and cycle-accurate descriptions in a single model. The feasibility and design efficiency of our approach is demonstrated with a number of contemporary, real-world processor architectures.

Retargetable C compilers are currently widely used to quickly obtain compiler support for new embedded processors and to perform early processor architecture exploration. A partially inherent problem of the retargetable compilation approach, though, is the limited code quality as compared to hand-written compilers or assembly code due to the lack of dedicated optimizations techniques. This problem can be circumvented by designing flexible, retargetable code optimization techniques that apply to a certain range of target architectures. This article focuses on target machines with SIMD instruction support, a common feature in embedded processors for multimedia applications. However, SIMD optimization is known to be a difficult task since SIMD architectures are largely nonuniform, support only a limited set of data types and impose several memory alignment constraints. Additionally, such techniques require complicated loop transformations, which are tailored to the SIMD architecture in order to exhibit the necessary amount of parallelism in the code. Thus, integrating the SIMD optimization and the required loop transformations together in a single retargeting formalism is an ambitious challenge. In this article, we present an efficient and quickly retargetable SIMD code optimization framework that is integrated into an industrial retargetable C compiler. Experimental results for different processors demonstrate that the proposed technique applies to real-life target machines and that it produces code quality improvements close to the theoretical limit.

Efficient architecture exploration and design of application specific instruction-set processors (ASIPs) requires retargetable software development tools, in particular C compilers that can be quickly adapted to new architectures. A widespread approach is to model the target architecture in a dedicated architecture description language (ADL) and to generate the tools automatically from the ADL specification. For C compiler generation, however, most existing systems are limited either by the manual retargeting effort or by redundancies in the ADL models that lead to potential inconsistencies. We present a new approach to retargetable compilation, based on the LISA 2.0 ADL with instruction semantics, that minimizes redundancies while simultaneously achieving a high degree of automation. The key of our approach is to generate the mapping rules needed in the compiler's code selector from the instruction semantics information. We describe the required analysis and generation techniques, and present experimental results for several embedded processors.