Vector processors are a very promising solution for mobile devices and servers due to their inherently energy-efficient way of exploiting data-level parallelism. Previous research on vector architectures predominantly focused on performance, so vector processors require a new design space exploration to achieve low power. In this paper, we present a design space exploration of adder unit for vector processors (VA), as it is one of the crucial components in the core design with a non-negligible impact in overall performance and power. For this interrelated circuit-architecture exploration, we developed a novel framework with both architectural- and circuit-level tools. Our framework includes both design- (e.g. adder's family type) and vector architecture-related parameters (e.g. vector length). Finally, we present guidelines on the selection of the most appropriate VA for different types of vector processors according to different sets of metrics of interest. For example, we found that 2-lane configurations are more EDP (Energy×Delay)-efficient than single lane configurations for low-end mobile processors.Peer ReviewedPostprint (published version

No abstract

No abstract

Graph500 is a data intensive application for high performance computing and it is an increasingly important workload because graphs are a core part of most analytic applications. So far there is no work that examines if Graph500 is suitable for vectorization mostly due a lack of vector memory instructions for irregular memory accesses. The Xeon Phi is a massively parallel processor recently released by Intel with new features such as a wide 512-bit vector unit and vector scatter/gather instructions. Thus, the Xeon Phi allows for more efficient parallelization of Graph500 that is combined with vectorization. In this paper we vectorize Graph500 and analyze the impact of vectorization and prefetching on the Xeon Phi. We also show that the combination of parallelization, vectorization and prefetching yields a speedup of 27% over a parallel version with prefetching that does not leverage the vector capabilities of the Xeon Phi.The research leading to these results has received funding from the\ud European Research Council under the European Unions 7th FP (FP/2007-\ud 2013) / ERC GA n. 321253. It has been partially funded by the Spanish\ud Government (TIN2012-34557)Peer ReviewedPostprint (published version

No abstract

Selecting an appropriate estimation method for a given technology and design is of crucial interest as the estimations guide future project and design decisions. The accuracy of the estimations of area, timing, and power (metrics of interest) depends on the phase of the design flow and the fidelity of the models. In this research, we use design space exploration of low-power adders as a case study for comparative analysis of two estimation flows: Physical layout Aware Synthesis (PAS) and Place and Route (PnR). We study and compare post-PAS and post-PnR estimations of the metrics of interest and the impact of various design parameters and input switching activity factor (αI). Adders are particularly interesting for this study because they are fundamental microprocessor units, and their design involves many parameters that create a vast design space. We show cases when the post-PAS and post-PnR estimations could lead to different design decisions, especially from a low-power designer point of view. Our experiments reveal that post-PAS results underestimate the side-effects of clock-gating, pipelining, and extensive timing optimizations compared to post-PnR results. We also observe that PnR estimation flow sometimes reports counterintuitive results

No abstract

No abstract