A Comparative Evaluation of Latency-Aware Energy Optimization Approaches in Many-Core Systems (Invited Paper)

Many applications vary a lot in execution time depending on their workload. A prominent example is image processing applications, where the execution time is dependent on the content or the size of the processed input images. An interesting case is when these applications have quality-of-service requirements such as soft deadlines, that they should meet as good as possible. A further complicated case is when such applications have one or even multiple further objectives to optimize like, e.g., energy consumption. Approaches that dynamically adapt the processing resources to application needs under multiple optimization goals and constraints can be characterized into the application-specific and feedback-based techniques. Whereas application-specific approaches typically statically use an offline stage to determine the best configuration for each known workload, feedback-based approaches, using, e.g., control theory, adapt the system without the need of knowing the effect of workload on these goals. In this paper, we evaluate a state-of-the-art approach of each of the two categories and compare them for image processing applications in terms of energy consumption and number of deadline misses on a given many-core architecture. In addition, we propose a second feedback-based approach that is based on finite state machines (FSMs). The obtained results suggest that whereas the state-of-the-art application-specific approach is able to meet a specified latency deadline whenever possible while consuming the least amount of energy, it requires a perfect characterization of the workload on a given many-core system. If such knowledge is not available, the feedback-based approaches have their strengths in achieving comparable energy savings, but missing deadlines more often

RAVEN: Reinforcement Learning for Generating Verifiable Run-Time Requirement Enforcers for MPSoCs

In embedded systems, applications frequently have to meet non-functional requirements regarding, e.g., real-time or energy consumption constraints, when executing on a given MPSoC target platform. Feedback-based controllers have been proposed that react to transient environmental factors by adapting the DVFS settings or degree of parallelism following some predefined control strategy. However, it is, in general, not possible to give formal guarantees for the obtained controllers to satisfy a given set of non-functional requirements. Run-time requirement enforcement has emerged as a field of research for the enforcement of non-functional requirements at run-time, allowing to define and formally verify properties on respective control strategies specified by automata. However, techniques for the automatic generation of such controllers have not yet been established. In this paper, we propose a technique using reinforcement learning to automatically generate verifiable feedback-based enforcers. For that, we train a control policy based on a representative input sequence at design time. The learned control strategy is then transformed into a verifiable enforcement automaton which constitutes our run-time control model that can handle unseen input data. As a case study, we apply the approach to generate controllers that are able to increase the probability of satisfying a given set of requirement verification goals compared to multiple state-of-the-art approaches, as can be verified by model checkers

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Isolation of an Elusive Phosphametallacyclobutadiene and Its Role in Reversible Carbon-Carbon Bond Cleavage

The reactivity of phosphaalkynes, the isolobal and isoelectronic congeners to alkynes, with metal alkylidyne complexes is explored in this work. Treating the tungsten alkylidyne [t BuOCO]W≡Ct Bu(THF)2 (1) with phosphaalkyne (10) results in the formation of [O2 C(t BuC=)W{η2 -(P,C)-P≡C-Ad}(THF)] (13-t BuTHF ) and [O2 C(AdC=)W{η2 -(P,C)-P≡C-t Bu}(THF)] (13-AdTHF ); derived from the formal reductive migratory insertion of the alkylidyne moiety into a W-Carene bond. Analogous to alkyne metathesis, a stable phosphametallacyclobutadiene complex [t BuOCO]W[κ2 -C(t Bu)PC(Ad)] (14) forms upon loss of THF from the coordination sphere of either 13-t BuTHF or 13-AdTHF . Remarkably, the C-C bonds reversibly form/cleave with the addition or removal of THF from the coordination sphere of the formal tungsten(VI) metal center, permitting unprecedented control over the transformation of a tetraanionic pincer to a trianionic pincer and back. Computational analysis offers thermodynamic and electronic reasoning for the reversible equilibrium between 13-t Bu/AdTHF and 14