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.

Retargetable C compilers are key components of today's embedded processor design platforms for quickly obtaining compiler support and performing early processor architecture exploration. The inherent problem of the retargetable compilation approach, though, is the well known trade-off between the compiler's flexibility and the quality of generated code. However, it can be circumvented by designing flexible, configurable code optimization techniques applicable to a certain range of target architectures. This paper focuses on target machines with predicated execution support which is wide-spread in deeply pipelined and highly parallel embedded processors used in next generation high-end video, multimedia and wireless devices. We present an efficient and quickly retargetable code optimization technique for predicated execution that is integrated into an industrial retargetable C compiler. Experimental results for several embedded processors demonstrate that the proposed technique is applicable to real-life target machines and that it produces significant code quality improvements for control intensive applications.

The conflicting requirements of performance and flexibility in today 's embedded system market are forcing system designers to use more and more of the so called configurable or customizable processor cores. Such processors tend to meet the demanding performance constraints by accommodating application specific instruction set extensions (ISEs) which have, naturally, become a vital component of current processor customization flows. One major bottleneck in maximizing ISE performance is the limitation on the data-bandwidth between the general purpose register (GPR) file and the ISEs. For improved performance, it is desirable to have a large data-bandwidth from the GPRs to ISEs. However, the tight area constraints of modern embedded processors often restrict the GPR I/O of ISEs to save port area of the register files. This paper presents a novel approach to increase the GPR I/O of ISEs without significantly increasing the size of the GPR files. This is achieved by applying the concept of register clustering, common in many VLIW architectures, to single-issue processors with high performance ISEs. Such clustering often causes extra register moves in compiled code. This work also presents an algorithm to minimize such register moves. The benchmark results presented in this paper show that our solution can significantly reduce the area overhead of many-port GPR files without sacrificing the performance improvements through ISEs.

Application-Specific Instruction-Set Processors (ASIPs) are becoming increasingly popular in the world of customized, application-driven System-on-Chip (SoC) designs. Efficient ASIP design requires an iterative architecture exploration loop---gradual refinement of the processor architecture starting from an initial template. To accomplish this task, design automation tools are used to detect bottlenecks in embedded applications, to implement application-specific processor instructions, and to automatically generate the required software tools (such as instruction-set simulator, C-compiler, assembler, and profiler), as well as to synthesize the hardware. This paper describes an architecture exploration loop for an ASIP coprocessor that implements common encryption functionality used in symmetric block cipher algorithms for internet protocol security (IPSec). The coprocessor is accessed via shared memory and, as a consequence, our approach is easily adaptable to arbitrary main processor architectures. This paper presents the extended version of our case study that has been already published on the SCOPES conference in 2004. In both papers, a MIPS architecture is used as the main processor and Blowfish as encryption algorithm.

Sophisticated C compiler support for network processors (NPUs) is required to improve their usability and consequently, their acceptance in system design. Nonetheless, high-level code compilation always introduces overhead, regarding code size and performance compared to handwritten assembly code. This overhead result partially from high-level function calls that usually introduce memory accesses in order to save and reload registers contents. A key feature of many NPU architectures is hardware multithreading support, in the form of separate register files, for fast context switching between different application tasks. In this paper, a new NPU code optimization technique to use such HW contexts is presented that minimizes the overhead for saving and reloading register contents for function calls via the runtime stack. The feasibility and the performance gain of this technique are demonstrated for the Infineon Technologies PP32 NPU architecture and typical network application kernels

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.

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 ADL-based 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 key tools for efficient architecture exploration for embedded processors. In this paper we describe a novel approach to retargetable compilation based on LISA, an industrial processor modeling language for efficient ASIP design. In order to circumvent the well-known trade-off between flexibility and code quality in retargetable compilation, we propose a user-guided, semiautomatic methodology that in turn builds on a powerful existing C compiler design platform. Our approach allows to include generated C compilers into the ASIP architecture exploration loop at an early stage, thereby allowing for a more efficient design process and avoiding application/architecture mismatches. We present the corresponding methodology and tool suite and provide experimental data for two real-life embedded processors that prove the feasibility of the approach.