On Timing Model Extraction and Hierarchical Statistical Timing Analysis

In this paper, we investigate the challenges to apply Statistical Static Timing Analysis (SSTA) in hierarchical design flow, where modules supplied by IP vendors are used to hide design details for IP protection and to reduce the complexity of design and verification. For the three basic circuit types, combinational, flip-flop-based and latch-controlled, we propose methods to extract timing models which contain interfacing as well as compressed internal constraints. Using these compact timing models the runtime of full-chip timing analysis can be reduced, while circuit details from IP vendors are not exposed. We also propose a method to reconstruct the correlation between modules during full-chip timing analysis. This correlation can not be incorporated into timing models because it depends on the layout of the corresponding modules in the chip. In addition, we investigate how to apply the extracted timing models with the reconstructed correlation to evaluate the performance of the complete design. Experiments demonstrate that using the extracted timing models and reconstructed correlation full-chip timing analysis can be several times faster than applying the flattened circuit directly, while the accuracy of statistical timing analysis is still well maintained

Spatio-temporal wavelet regularization for parallel MRI reconstruction: application to functional MRI

Parallel MRI is a fast imaging technique that enables the acquisition of highly resolved images in space or/and in time. The performance of parallel imaging strongly depends on the reconstruction algorithm, which can proceed either in the original k-space (GRAPPA, SMASH) or in the image domain (SENSE-like methods). To improve the performance of the widely used SENSE algorithm, 2D- or slice-specific regularization in the wavelet domain has been deeply investigated. In this paper, we extend this approach using 3D-wavelet representations in order to handle all slices together and address reconstruction artifacts which propagate across adjacent slices. The gain induced by such extension (3D-Unconstrained Wavelet Regularized -SENSE: 3D-UWR-SENSE) is validated on anatomical image reconstruction where no temporal acquisition is considered. Another important extension accounts for temporal correlations that exist between successive scans in functional MRI (fMRI). In addition to the case of 2D+t acquisition schemes addressed by some other methods like kt-FOCUSS, our approach allows us to deal with 3D+t acquisition schemes which are widely used in neuroimaging. The resulting 3D-UWR-SENSE and 4D-UWR-SENSE reconstruction schemes are fully unsupervised in the sense that all regularization parameters are estimated in the maximum likelihood sense on a reference scan. The gain induced by such extensions is illustrated on both anatomical and functional image reconstruction, and also measured in terms of statistical sensitivity for the 4D-UWR-SENSE approach during a fast event-related fMRI protocol. Our 4D-UWR-SENSE algorithm outperforms the SENSE reconstruction at the subject and group levels (15 subjects) for different contrasts of interest (eg, motor or computation tasks) and using different parallel acceleration factors (R=2 and R=4) on 2x2x3mm3 EPI images.Comment: arXiv admin note: substantial text overlap with arXiv:1103.353

When, How Fast and by How Much do Trade Costs change in the Euro Area?

Microfoundations of the euro’s effect on euro area trade hinge on the timing, the speed and the size of adjustment in trade costs. We estimate timing, speed and size of adjustment in trade costs for sectoral trade data. Our approach allows for sector specific impacts of trade costs on sectoral trade while controlling for unobserved but time-variant variables at the sector level. We find that, due to falling trade costs, trade within the euro area increases between the years 2000 and 2003 by 10 to 20 percent compared with trade between European countries that are not members of the euro area. Adjustment of individual sectors is extremely fast whereas aggregate adjustment spreads out because different sectors adjust at distinct times.Euro trade effect, gravity model, smooth transition, Kalman filter

A Survey on Compiler Autotuning using Machine Learning

Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily enhance the quality of the obtained results and, more importantly, make it feasible to tackle two main compiler optimization problems: optimization selection (choosing which optimizations to apply) and phase-ordering (choosing the order of applying optimizations). The compiler optimization space continues to grow due to the advancement of applications, increasing number of compiler optimizations, and new target architectures. Generic optimization passes in compilers cannot fully leverage newly introduced optimizations and, therefore, cannot keep up with the pace of increasing options. This survey summarizes and classifies the recent advances in using machine learning for the compiler optimization field, particularly on the two major problems of (1) selecting the best optimizations and (2) the phase-ordering of optimizations. The survey highlights the approaches taken so far, the obtained results, the fine-grain classification among different approaches and finally, the influential papers of the field.Comment: version 5.0 (updated on September 2018)- Preprint Version For our Accepted Journal @ ACM CSUR 2018 (42 pages) - This survey will be updated quarterly here (Send me your new published papers to be added in the subsequent version) History: Received November 2016; Revised August 2017; Revised February 2018; Accepted March 2018

When, how fast and by how much do trade costs change in the euro area?

Microfoundations of the euro's effect on euro area trade hinge on the timing, the speed and the size of adjustment in trade costs. We estimate timing, speed and size of adjustment in trade costs for sectoral trade data. Our approach allows for sector specific impacts of trade costs on sectoral trade while controlling for unobserved but time-variant variables at the sector level. We find that, due to falling trade costs, trade within the euro area increases between the years 2000 and 2003 by 10 to 20 percent compared with trade between European countries that are not members of the euro area. Adjustment of individual sectors is extremely fast whereas aggregate adjustment spreads out because different sectors adjust at distinct times. --

When, how fast and by how much do trade costs change in the euro area?

Microfoundations of the euro's effect on euro area trade hinge on the timing, the speed and the size of adjustment in trade costs. We estimate timing, speed and size of adjustment in trade costs for sectoral trade data. Our approach allows for sector specific impacts of trade costs on sectoral trade while controlling for unobserved but time-variant variables at the sector level. We find that, due to falling trade costs, trade within the euro area increases between the years 2000 and 2003 by 10 to 20 percent compared with trade between European countries that are not members of the euro area. Adjustment of individual sectors is extremely fast whereas aggregate adjustment spreads out because different sectors adjust at distinct times. --