The continuous growth of digital integrated designs demands constant improvement in tools and development processes. Engineering change order (ECO) are design changes that occur late in the design process and require that subsequent stages must be adapted. ECO changes after the place and route flow can result in a large number of disconnected components and design tools are expected to reconnect these components on the fly. The ICCAD 2017 contest problem B launched a race to solve this challenge. This article presents two new solutions that outperform the top published solutions for this problem, with reduced routing costs and 21% shorter execution time. Moreover, our solutions are simpler, more general and pave the way for optimal minimum spanning tree-based obstacle-avoiding component-to-component routing.

For real-time tasks, cache behavior must be constrained via cache locking or predicted by WCET analysis. Since the former gives up energy efficiency for predictability, this paper proposes a novel code optimization that reduces the miss rate of unlocked instruction caches and, provenly, does not increase the WCET. We optimized the 37 programs from the Mälardalen WCET benchmark for 36 cache configurations and two technologies. By exploiting software prefetching on top of on-demand fetching, we reduced the memory's contribution to the energy consumption (by 11.2%), to the average case execution time (by 10.2%), and to the WCET (by 17.4%).

Although pel decimation has been widely used to reduce the computational effort in video coding, there is no consensus about the optimal subsampling pattern. This paper presents an extensive analytical and statistical comparison of several different subsampling patterns using analysis of variance. The investigation includes commonly used patterns as well as seven proposed ones. The experiments were conducted on 19 video samples in a range of five resolutions (being nine videos at 1080p) and 30 bitrates by using the state-of-the-art x264 encoder running successive elimination exhaustive search. Two objective quality metrics were reported, PSNR and DSSIM, resulting in 10680 experimental points. The analysis of such amount of data allowed us to conclude that the proposed 4:3 ratio shows less than 5% in DSSIM and 1% in PSNR losses, being more than two times faster than full sampling. Compared with higher decimation, it presents a better trade-off between speedup and quality loss.