Restructuring of ArchC for integration to TLM-based project

Orientador: Rodolfo Jardim de AzevedoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O surgimento dos SoCs (Systems-on-Chip) levou ao desenvolvimento das metodologias de projeto baseadas em TLM (Transaction-Level Modelling), que oferecem diversas etapas de modelagem intermediárias entre a especificação pura e a descrição sintetizável RTL (Register Transfer Level ), tornando mais tratável o projeto de sistemas dessa complexidade. Levando-se em consideração que esses sistemas geralmente possuem microprocessadores como módulos principais, torna-se desejável o uso de linguagens de descrição de arquiteturas (ADLs ? Architecture Description Languages) como ArchC e suas ferramentas para que seja possível modelar esses processadores e gerar módulos simuladores para eles em uma fração do tempo tradicionalmente gasto com essa tarefa. Porém, ArchC, em sua penúltima versão, a 1.6, possui utilidade limitada para esse fim, pois os simuladores que é capaz de gerar são autocontidos, não sendo facilmente integráveis aos modelos TLM em nível de sistema como um todo. Este trabalho consiste em uma remodelagem da linguagem ArchC e sua ferramenta acsim de modo a acrescentar essa capacidade de integração aos simuladores funcionais interpretados que é capaz de gerar, dando assim origem à versão 2.0 de ArchCAbstract: The advent of SoCs (Systems-on-Chip) lead to the development of project methodologies based on TLM (Transaction-Level Modelling), which consist of several modelling layers between pure specifications and synthesizable RTL (Register Transfer Level ) descriptions, making the complexity of such systems more manageable. Considering that those systems usually have microprocessors as main modules, it is desirable to use architecture description languages (ADLs) like ArchC and its toolkit to model those processors and generate simulator modules for them in a fraction of the time usually spent in that task. However, ArchC, in its previous version, 1.6, has limitations for that use, since the simulators it generates are self-contained, thus hard to integrate to TLM system-level models. This work consists in remodelling ArchC and its acsim tool, adding this ability of integration to its functional interpreted simulators, leading to version 2.0 of ArchCMestradoSistemas de ComputaçãoMestre em Ciência da Computaçã

Exploration of the scalability of SIMD processing for software defined radio

The idea of software defined radio (SDR) describes a signal processing system for wireless communications that allows performing major parts of the physical layer processing in software. SDR systems are more flexible and have lower development costs than traditional systems based on application-specific integrated circuits (ASICs). Yet, SDR requires programmable processor architectures that can meet the throughput and energy efficiency requirements of current third generation (3G) and future fourth generation (4G) wireless standards for mobile devices. Single instruction, multiple data (SIMD) processors operate on long data vectors in parallel data lanes and can achieve a good ratio of computing power to energy consumption. Hence, SIMD processors could be the basis of future SDR systems. Yet, SIMD processors only achieve a high efficiency if all parallel data lanes can be utilized. This thesis investigates the scalability of SIMD processing for algorithms required in 4G wireless systems; i. e. the scaling of performance and energy consumption with increasing SIMD vector lengths is explored. The basis of the exploration is a scalable SIMD processor architecture, which also supports long instruction word (LIW) execution and can be configured with four different permutation networks for vector element permutations. Radix-2 and mixed-radix fast Fourier transform (FFT) algorithms, sphere decoding for multiple input, multiple output (MIMO) systems, and the decoding of quasi-cyclic lowdensity parity check (LDPC) codes have been examined, as these are key algorithms for 4G wireless systems. The results show that the performance of all algorithms scales with the SIMD vector length, yet there are different constraints on the ratios between algorithm and architecture parameters. The radix-2 FFT algorithm allows close to linear speedups if the FFT size is at least twice the SIMD vector length, the mixed-radix FFT algorithm requires the FFT size to be a multiple of the squared SIMD width. The performance of the implemented sphere decoding algorithm scales linearly with the SIMD vector length. The scalability of LDPC decoding is determined by the expansion factor of the quasicyclic code. Wider SIMD processors offer better performance and also require less energy than processors with a shorter vector length for all considered algorithms. The results for different permutations networks show that a simple permutation network is sufficient for most applications