Abstract-We propose a self-contained, flat, forcedirected algorithm for global placement that is simpler than existing placers and easier to integrate into timingclosure flows. It maintains lower-bound and upper-bound placements that converge to a final solution. The upperbound placement is produced by a novel rough legalization algorithm. Our placer SimPL outperforms mPL6, NTUPlace3, FastPlace3, APlace2 and Capo simultaneously in runtime and solution quality, running 6.4 times faster than mPL6 and reducing wirelength by 2% on the ISPD 2005 benchmark suite. I. INTRODUCTIONGlobal placement currently remains at the core of physical design and is a gating factor for downstream optimizations during timing closure [2]. Despite impressive improvements reported by researchers [15] and industry software in the last five years, state-ofthe-art algorithms and tools for placement suffer several key shortcomings which are becoming more pronounced at recent technology nodes. These shortcomings fall into four categories: (i) speed, (ii) solution quality, (iii) simplicity and integration with other optimizations, (iv) support for multithreaded execution. We propose the SimPL algorithm that simultaneously improves results in the first three categories and lends itself naturally to parallelism on multicore CPUs. [6]. Forcedirected algorithms model total net length by a quadratic function of cell locations and minimize it by solving a large sparse system of linear equations. To discourage cell overlap, forces are added pulling cells away from high-density areas. These forces are modeled by pseudopins and pseudonets, which extend the original quadratic function [11]. They are updated after each linear-system solve until iterations converge. Non-linear optimization models net length by more sophisticated differentiable functions with linear asymptotic behavior which are then minimized by advanced numerical analysis techniques [12]. Cell density is modeled by functional terms, which are more accurate than forces, but also require updates after each change to placement [7], [12]. Algorithms in both categories are directly used in the industry or closely resemble those in industry placers.
Background Few studies have compared the outcomes of endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) in patients with early gastric cancer. Methods We studied 780 lesions for which endoscopic treatment was indicated according to the Japanese Gastric Cancer Association (JGCA) criteria or the Results The median follow-up was 73 months in the EAM group and 65 months in the ESD group. Overall, the local recurrence rate was significantly lower in the ESD group (0.2 %, 1/421) than in the EAM group (4.2 %, 15/359) (p \ 0.05). For lesions meeting the JGCA criteria, the local recurrence rate was 2.9 % in the EAM group and 0 % in the ESD group (p \ 0.05). For lesions meeting the NCC criteria, the local recurrence rate was 12.5 % in the EAM group and 0.6 % in the ESD group (p \ 0.05). There was no significant difference between the groups in overall survival. Conclusions On long-term follow-up, ESD was associated with a lower rate of local recurrence than EAM for lesions that met the JGCA or the NCC criteria. From the point of view of radical curability, ESD can be recommended for the management of lesions that meet either set of criteria.
The well-studied gate-sizing optimization is a major contributor to IC power-performance tradeoffs. Viable optimizers must accurately model circuit timing, satisfy a variety of constraints, scale to large circuits, and effectively utilize a large (but finite) number of possible gate configurations, including V t and L g . Within the research-oriented infrastructure used in the ISPD 2012 Gate Sizing Contest, we develop a metaheuristic approach to gate sizing that integrates timing and power optimization, and handles several types of constraints. Our solutions are evaluated using a rigorous protocol that computes circuit delay with Synopsys PrimeTime. Our implementation Trident outperforms the best-reported results on all but one of the ISPD 2012 benchmarks. Compared to the 2012 contest winner, we further reduce leakage power by an average of 43%.
Several clinicopathological features of clear cell renal cell carcinomas (ccRCC) contribute to make an “atypical” cancer, including resistance to chemotherapy, sensitivity to anti-angiogenesis therapy and ICIs despite a low mutational burden, and CD8+ T cell infiltration being the predictor for poor prognosis–normally CD8+ T cell infiltration is a good prognostic factor in cancer patients. These “atypical” features have brought researchers to investigate the molecular and immunological mechanisms that lead to the increased T cell infiltrates despite relatively low molecular burdens, as well as to decipher the immune landscape that leads to better response to ICIs. In the present study, we summarize the past and ongoing pivotal clinical trials of immunotherapies for ccRCC, emphasizing the potential molecular and cellular mechanisms that lead to the success or failure of ICI therapy. Single-cell analysis of ccRCC has provided a more thorough and detailed understanding of the tumor immune microenvironment and has facilitated the discovery of molecular biomarkers from the tumor-infiltrating immune cells. We herein will focus on the discussion of some major immune cells, including T cells and tumor-associated macrophages (TAM) in ccRCC. We will further provide some perspectives of using molecular and cellular biomarkers derived from these immune cell types to potentially improve the response rate to ICIs in ccRCC patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.