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At least 955 records · Page 53

MO-FG-CAMPUS-TeP3-01: A Model of Baseline Shift to Improve Robustness of Proton Therapy Treatments of Moving Tumors

Purpose: The shift in mean position of a moving tumor also known as “baseline shift”, has been modeled, in order to automatically generate uncertainty scenarios for the assessment and robust optimization of proton therapy treatments in lung cancer. Methods: An average CT scan and a Mid-Position CT scan (MidPCT) of the patient at the planning time are first generated from a 4D-CT data. The mean position of the tumor along the breathing cycle is represented by the GTV contour in the MidPCT. Several studies reported both systematic and random variations of the mean tumor position from fraction to fraction. Our model can simulate this baseline shift by generating a local deformation field that moves the tumor on all phases of the 4D-CT, without creating any non-physical artifact. The deformation field is comprised of normal and tangential components with respect to the lung wall in order to allow the tumor to slip within the lung instead of deforming the lung surface. The deformation field is eventually smoothed in order to enforce its continuity. Two 4D-CT series acquired at 1 week of interval were used to validate the model. Results: Based on the first 4D-CT set, the model was able to generate a third 4D-CT that reproduced the 5.8 mm baseline-shift measured in the second 4D-CT. Water equivalent thickness (WET) of the voxels have been computed for the 3 average CTs. The root mean square deviation of the WET in the GTV is 0.34 mm between week 1 and week 2, and 0.08 mm between the simulated data and week 2. Conclusion: Our model can be used to automatically generate uncertainty scenarios for robustness analysis of a proton therapy plan. The generated scenarios can also feed a TPS equipped with a robust optimizer. Kevin Souris, Ana Barragan, and Dario Di Perri are financially supported by Televie Grants from F.R.S.-FNRS.

60 APPLIED LIFE SCIENCES↗

WE-AB-207A-08: BEST IN PHYSICS (IMAGING): Advanced Scatter Correction and Iterative Reconstruction for Improved Cone-Beam CT Imaging On the TrueBeam Radiotherapy Machine

Purpose: To improve CBCT image quality for image-guided radiotherapy by applying advanced reconstruction algorithms to overcome scatter, noise, and artifact limitations Methods: CBCT is used extensively for patient setup in radiotherapy. However, image quality generally falls short of diagnostic CT, limiting soft-tissue based positioning and potential applications such as adaptive radiotherapy. The conventional TrueBeam CBCT reconstructor uses a basic scatter correction and FDK reconstruction, resulting in residual scatter artifacts, suboptimal image noise characteristics, and other artifacts like cone-beam artifacts. We have developed an advanced scatter correction that uses a finite-element solver (AcurosCTS) to model the behavior of photons as they pass (and scatter) through the object. Furthermore, iterative reconstruction is applied to the scatter-corrected projections, enforcing data consistency with statistical weighting and applying an edge-preserving image regularizer to reduce image noise. The combined algorithms have been implemented on a GPU. CBCT projections from clinically operating TrueBeam systems have been used to compare image quality between the conventional and improved reconstruction methods. Planning CT images of the same patients have also been compared. Results: The advanced scatter correction removes shading and inhomogeneity artifacts, reducing the scatter artifact from 99.5 HU to 13.7 HU in a typical pelvis case. Iterative reconstruction provides further benefit by reducing image noise and eliminating streak artifacts, thereby improving soft-tissue visualization. In a clinical head and pelvis CBCT, the noise was reduced by 43% and 48%, respectively, with no change in spatial resolution (assessed visually). Additional benefits include reduction of cone-beam artifacts and reduction of metal artifacts due to intrinsic downweighting of corrupted rays. Conclusion: The combination of an advanced scatter correction with iterative reconstruction substantially improves CBCT image quality. It is anticipated that clinically acceptable reconstruction times will result from a multi-GPU implementation (the algorithms are under active development and not yet commercially available). All authors are employees of and (may) own stock of Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

Crystal Structure of a CRISPR RNA-guided Surveillance Complex Bound to a ssDNA Target

In prokaryotes, RNA derived from type I and type III CRISPR loci direct large ribonucleoprotein complexes to destroy invading bacteriophage and plasmids. In Escherichia coli, this 405-kilodalton complex is called Cascade. We report the crystal structure of Cascade bound to a single-stranded DNA (ssDNA) target at a resolution of 3.03 angstroms. The structure reveals that the CRISPR RNA and target strands do not form a double helix but instead adopt an underwound ribbon-like structure. This noncanonical structure is facilitated by rotation of every sixth nucleotide out of the RNA-DNA hybrid and is stabilized by the highly interlocked organization of protein subunits. These studies provide insight into both the assembly and the activity of this complex and suggest a mechanism to enforce fidelity of target binding.

59 BASIC BIOLOGICAL SCIENCES↗

Horizontal transfer of chromosomal DNA mediated by an integrative and conjugative element generates frequent localized recombination in Novosphingobium aromaticivorans

Horizontal gene transfer is an important evolutionary process by which DNA is exchanged between cells that are physically co-located but not direct evolutionary descendants. Horizontal transfer of highly divergent DNA is relatively easy to detect and can produce major phenotypic changes, exemplified by the acquisition of antibiotic resistance determinants. However, transfer of high-identity DNA, for example, between strains of the same species, is likely to be more frequent, harder to detect, and highly impactful in aggregate. In this work, we demonstrate that soil isolates of the alphaproteobacterium Novosphingobium aromaticivorans can exchange chromosomal DNA, leading to multiple unselected recombination events spanning approximately 10% of the chromosome. Chromosomal recombination was directional and more efficient near an integrative and conjugative element (ICE), and required a relaxase found in the ICE. Recombination could not be observed in strains from closely related Novosphingobium species. In combination, these results suggest that ICE-mediated recombination can efficiently recombine DNA within N. aromaticivorans, increasing the adaptive potential of the species while also enforcing species boundaries through preferential intraspecific recombination.

Allemann, Marco [ORNL]↗

A Mesorhizobium japonicum quorum sensing circuit that involves three linked genes and an unusual acyl-homoserine lactone signal

ABSTRACT Members of the genus Mesorhizobium, which are core components of the rhizosphere and specific symbionts of legume plants, possess genes for acyl-homoserine lactone (AHL) quorum sensing (QS). Here we show Mesorhizobium japonicum MAFF 303099 (formerly M. loti ) synthesizes and responds to N -[(2 E , 4 E )-2,4-dodecadienoyl] homoserine lactone (2 E, 4 E- C 12:2 -HSL). We show that the 2 E, 4 E- C 12:2 -HSL QS circuit involves one of four luxR-luxI -type genes found in the sequenced genome of MAFF 303099. We refer to this circuit, which appears to be conserved among Mesorhizobium species, as R1-I1. We show that two other Mesorhizobium strains also produce 2 E, 4 E- C 12:2 -HSL. The 2 E, 4 E- C 12:2 -HSL is unique among known AHLs in its arrangement of two trans double bonds. The R1 response to 2 E, 4 E- C 12:2 -HSL is extremely selective in comparison with other LuxR homologs, and the trans double bonds appear critical for R1 signal recognition. Most well-studied LuxI-like proteins use S -adenosylmethionine and an acyl-acyl carrier protein as substrates for synthesis of AHLs. Others that form a subgroup of LuxI-type proteins use acyl-coenzyme A substrates rather than acyl-acyl carrier proteins. I1 clusters with the acyl-coenzyme A-type AHL synthases. We show that a gene linked to the I1 AHL synthase is involved in the production of the QS signal. The discovery of the unique I1 product enforces the view that further study of acyl-coenzyme A-dependent LuxI homologs will expand our knowledge of AHL diversity. The involvement of an additional enzyme in AHL generation leads us to consider this system a three-component QS circuit. IMPORTANCE We report a Mesorhizobium japonicum quorum sensing (QS) system involving a novel acyl-homoserine lactone (AHL) signal. This system is known to be involved in root nodule symbiosis with host plants. The chemistry of the newly described QS signal indicated that there may be a dedicated cellular enzyme involved in its synthesis in addition to the types known for production of other AHLs. Indeed, we report that an additional gene is required for synthesis of the unique signal, and we propose that this is a three-component QS circuit as opposed to the canonical two-component AHL QS circuits. The signaling system is exquisitely selective. The selectivity may be important when this species resides in the complex microbial communities around host plants and may make this system useful in various synthetic biology applications of QS circuits.

59 BASIC BIOLOGICAL SCIENCES↗

Synthesis and crystal structures of inclusion compounds of 2,2'-dithiosalicylic acid and triethylamine/tripropylamine

Herein we reported two new inclusion compounds of 2,2'-dithiosalicylic acid (C{sub 14}H{sub 10}O{sub 4}S{sub 2}, DTSA) and triethylamine and tripropylamine, [C{sub 14}H{sub 8}O{sub 4}S{sub 2}{sup 2-} · [N{sup +}(C{sub 2}H{sub 5}){sub 3}]{sub 2} · H{sub 2}O] (1) and [C{sub 14}H{sub 10}O{sub 4}S{sub 2} · C{sub 14}H{sub 8}O{sub 4}S{sub 2}{sup 2-} · [N{sup +}(C{sub 3}H{sub 7}){sub 3}]{sub 2}] (2). Compound 1: triclinic P1̄, a = 8.2159(2), b = 12.5724(3), c = 14.9203(3) Å, α = 97.0390(10), β = 101.4310(10)°, γ = 101.3370(10)°, V = 1460.06(6) Å{sup 3}, Z = 2, R{sub 1} = 0.0526, wR{sub 2} = 0.1495; Compound 2: monoclinic P2{sub 1}/c, a = 20.5178(13), b = 15.3623(8), c = 15.5529(9) Å, β = 102.036(3)°, V = 4794.5(5) Å{sup 3}, Z = 4, R{sub 1} = 0.0533, wR{sub 2} = 0.1252. In these two crystal structures, DTSA utilizes conventional O–H···O hydrogen bonds to link to generate varied host lattices, in which the central N atoms of the guest amine molecules accept the protons of DTSA to form the corresponding cations to act as the couterions to develop the stable crystal structures. Noticeably, except Van der Waals forces usually existing between the host and guest molecules, the central N atoms of the guests of the two compounds can construct strong N–H…O hydrogen bonds with the related host molecules, which further enforce the host-guest interactions to help form the final inclusion compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Drug providers’ perspectives on antibiotic misuse practices in eastern Ethiopia: a qualitative study

Objective Antibiotic misuse includes using them to treat colds and influenza, obtaining them without a prescription, not finishing the prescribed course and sharing them with others. Although drug providers are well positioned to advise clients on proper stewardship practices, antibiotic misuse continues to rise in Ethiopia. It necessitates an understanding of why drug providers failed to limit such risky behaviours. This study aimed to explore drug providers’ perspectives on antibiotic misuse practices in eastern Ethiopia. Setting The study was conducted in rural Haramaya district and Harar town, eastern Ethiopia. Design and participants An exploratory qualitative study was undertaken between March and June 2023, among the 15 drug providers. In-depth interviews were conducted using pilot-tested, semistructured questions. The interviews were transcribed verbatim, translated into English and analysed thematically. The analyses considered the entire dataset and field notes. Results The study identified self-medication pressures, non-prescribed dispensing motives, insufficient regulatory functions and a lack of specific antibiotic use policy as the key contributors to antibiotic misuse. We found previous usage experience, a desire to avoid extra costs and a lack of essential diagnostics and antibiotics in public institutions as the key drivers of non-prescribed antibiotic access from private drug suppliers. Non-prescribed antibiotic dispensing in pharmacies was driven by client satisfaction, financial gain, business survival and market competition from informal sellers. Antibiotic misuse in the setting has also been linked to traditional and ineffective dispensing audits, inadequate regulatory oversights and policy gaps. Conclusion This study highlights profits and oversimplified access to antibiotics as the main motivations for their misuse. It also identifies the traditional antibiotic dispensing audit as an inefficient regulatory operation. Hence, enforcing specific antibiotic usage policy guidance that entails an automated practice audit, a responsible office and insurance coverage for persons with financial limitations can help optimise antibiotic use while reducing resistance consequences.

General & Internal Medicine↗

Local polynomial chaos expansion for linear differential equations with high dimensional random inputs

In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. Furthermore, the local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained from the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In our paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.

97 MATHEMATICS AND COMPUTING↗

Algorithms for propagating uncertainty across heterogeneous domains

We address an important research area in stochastic multi-scale modeling, namely the propagation of uncertainty across heterogeneous domains characterized by partially correlated processes with vastly different correlation lengths. This class of problems arise very often when computing stochastic PDEs and particle models with stochastic/stochastic domain interaction but also with stochastic/deterministic coupling. The domains may be fully embedded, adjacent or partially overlapping. The fundamental open question we address is the construction of proper transmission boundary conditions that preserve global statistical properties of the solution across different subdomains. Often, the codes that model different parts of the domains are black-box and hence a domain decomposition technique is required. No rigorous theory or even effective empirical algorithms have yet been developed for this purpose, although interfaces defined in terms of functionals of random fields (e.g., multi-point cumulants) can overcome the computationally prohibitive problem of preserving sample-path continuity across domains. The key idea of the different methods we propose relies on combining local reduced-order representations of random fields with multi-level domain decomposition. Specifically, we propose two new algorithms: The first one enforces the continuity of the conditional mean and variance of the solution across adjacent subdomains by using Schwarz iterations. The second algorithm is based on PDE-constrained multi-objective optimization, and it allows us to set more general interface conditions. The effectiveness of these new algorithms is demonstrated in numerical examples involving elliptic problems with random diffusion coefficients, stochastically advected scalar fields, and nonlinear advection-reaction problems with random reaction rates.

Cho, Heyrim↗

Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints

Here, we propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a linear program with complementarity constraints in order to obtain an estimate of the active set. The algorithm enforces descent on the objective function to promote global convergence to B-stationary points. We provide a convergence analysis and preliminary numerical results on a range of test problems. We also study the effect of fixing the active constraints in a bound-constrained quadratic program that can be solved on each iteration in order to obtain fast convergence.

97 MATHEMATICS AND COMPUTING↗

Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments

Here, we present a novel stochastic approach to binary optimization suited for optimal experimental design (OED) for Bayesian inverse problems governed by mathematical models such as partial differential equations. The OED utility function, namely, the regularized optimality criterion, is cast into a stochastic objective function in the form of an expectation over a multivariate Bernoulli distribution. The probabilistic objective is then solved by using a stochastic optimization routine to find an optimal observational policy. This formulation (a) is generally applicable to binary optimization problems with soft constraints and is ideal for OED and sensor placement problems; (b) does not require differentiability of the original objective function (e.g., a utility function in OED applications) with respect to the design variable, and thus it enables direct employment of sparsity-enforcing penalty functions such as $\ell_0$, without needing to utilize a continuation procedure or apply a rounding technique; (c) exhibits much lower computational cost than traditional gradient-based relaxation approaches; and (d) can be applied to both linear and nonlinear OED problems with proper choice of the utility function. The proposed approach is analyzed from an optimization perspective with detailed convergence analysis of the optimization approach and is also analyzed from a machine learning perspective with correspondence to policy gradient reinforcement learning. The approach is demonstrated numerically by using an idealized two-dimensional Bayesian linear inverse problem and validated by extensive numerical experiments carried out for sensor placement in a parameter identification setup.

97 MATHEMATICS AND COMPUTING↗

A Fourth-Order Embedded Boundary Finite Volume Method for the Unsteady Stokes Equations with Complex Geometries

A fourth-order finite volume embedded boundary (EB) method is presented for the unsteady Stokes equations. The algorithm represents complex geometries on a Cartesian grid using EB, employing a technique to mitigate the ``small cut-cell"" problem without mesh modifications, cell merging, or state redistribution. Spatial discretizations are based on a weighted least-squares technique that has been extended to fourth-order operators and boundary conditions, including an approximate projection to enforce the divergence-free constraint. Solutions are advanced in time using a fourth-order additive implicit-explicit Runge-Kutta method, with the viscous and source terms treated implicitly and explicitly, respectively. Formal accuracy of the method is demonstrated with several grid convergence studies, and results are shown for an application with a complex bio-inspired material. In conclusion, the developed method achieves fourth-order accuracy and is stable despite the pervasive small cells arising from complex geometries.

97 MATHEMATICS AND COMPUTING↗

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

Dirichlet-to-Neumann maps enable the coupling of multiphysics simulations across computational subdomains by ensuring continuity of state variables and fluxes at artificial interfaces. We present a novel method for learning Dirichlet-to-Neumann maps on graphs using Gaussian processes, specifically for problems where the data obey a conservation law arising from an underlying partial differential equation. Our approach combines discrete exterior calculus and nonlinear optimal recovery to infer relationships between vertex and edge values. This framework yields data-driven predictions with uncertainty quantification across the entire graph, even when observations are limited to a subset of vertices and edges. By minimizing the reproducing kernel Hilbert space norm while penalizing kernel complexity through maximum likelihood estimation, our method ensures that the resulting surrogate strictly enforces conservation laws without overfitting. We demonstrate our method on two representative applications: subsurface flow in fracture networks and arterial blood flow. Finally, the results demonstrate that the method maintains high accuracy and well-calibrated uncertainty estimates even under severe data scarcity, highlighting its potential for scientific applications where limited data and reliable uncertainty quantification are critical.

Dirichlet-to-Neumann map↗

Statistical (n,$$\gamma $$) cross section model comparison for short-lived nuclei

Abstract Neutron-capture cross sections of neutron-rich nuclei are calculated using a Hauser–Feshbach model when direct experimental cross sections cannot be obtained. A number of codes to perform these calculations exist, and each makes different assumptions about the underlying nuclear physics. We investigated the systematic uncertainty associated with the choice of Hauser-Feshbach code used to calculate the neutron-capture cross section of a short-lived nucleus. The neutron-capture cross section for $$^{73}\hbox {Zn}$$ 73 Zn (n, $$\gamma $$ γ ) $$^{74}\hbox {Zn}$$ 74 Zn was calculated using three Hauser-Feshbach statistical model codes: TALYS, CoH, and EMPIRE. The calculation was first performed without any changes to the default settings in each code. Then an experimentally obtained nuclear level density (NLD) and $$\gamma $$ γ -ray strength function ( $$\gamma \hbox {SF}$$ γ SF ) were included. Finally, the nuclear structure information was made consistent across the codes. The neutron-capture cross sections obtained from the three codes are in good agreement after including the experimentally obtained NLD and $$\gamma \hbox {SF}$$ γ SF , accounting for differences in the underlying nuclear reaction models, and enforcing consistent approximations for unknown nuclear data. It is possible to use consistent inputs and nuclear physics to reduce the differences in the calculated neutron-capture cross section from different Hauser-Feshbach codes. However, ensuring the treatment of the input of experimental data and other nuclear physics are similar across multiple codes requires a careful investigation. For this reason, more complete documentation of the inputs and physics chosen is important.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Constraints in Quantum Geometrodynamics

We compare different treatments of the constraints in canonical quantum gravity. The standard approach on the superspace of 3-geometries treats the constraints as the sole carriers of the dynamic content of the theory, thus rendering the traditional dynamical equations obsolete. Quantization of the constraints in both the Dirac and ADM square root Hamiltonian approaches leads to the well known problems of time evolution. These problems of time are of both an interpretational and technical nature. In contrast, the geometrodynamic quantization procedure on the superspace of the true dynamical variables separates the issues of quantization from the enforcement of the constraints. The resulting theory takes into account states that are off-shell with respect to the constraints, and thus avoids the problems of time. We develop, for the first time, the geometrodynamic quantization formalism in a general setting and show that it retains all essential features previously illustrated in the context of homogeneous cosmologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

How low can vacuum energy go when your fields are finite-dimensional?

According to the holographic bound, there is only a finite density of degrees of freedom in space when gravity is taken into account. Conventional quantum field theory does not conform to this bound, since in this framework, infinitely many degrees of freedom may be localized to any given region of space. In this paper, we explore the viewpoint that quantum field theory may emerge from an underlying theory that is locally finite-dimensional, and we construct a locally finite-dimensional version of a Klein–Gordon scalar field using generalized Clifford algebras. Demanding that the finite-dimensional field operators obey a suitable version of the canonical commutation relations makes this construction essentially unique. Lastly, we then find that enforcing local finite dimensionality in a holographically consistent way leads to a huge suppression of the quantum contribution to vacuum energy, to the point that the theoretical prediction becomes plausibly consistent with observations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Temperature uncertainty modelling with proxy structural data as geostatistical constraints for well siting: an example applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural geology information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aims of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations. The data used to support the modelling are measured temperatures and structural proxies from 3D geologic modelling (distance to fault, distance to fault intersections and terminations, Coulomb stress change and dilation tendency), the latter considered ‘secondary’ data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally-likely temperature models (i.e. realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: V prior and entropy. V prior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because of the dipping ellipsoid shape created and that the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e. linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g. dilation v. distance to fault termination) should be used given the specific geothermal system. In general, V prior from local varying mean results identify locations that are close to high values for the structural proxies: areas with higher probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comparison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

15 GEOTHERMAL ENERGY↗

Enhancing the Performance of Assisted Execution Runtime Systems through Hardware/Software Techniques

To meet the expected performance, future exascale systems will require programmers to increase the level of parallelism of their applications. Novel programming models simplify parallel programming at the cost of increasing runtime overheard. Assisted execution models have the potential of reducing this overhead but they generally also reduce processor utilization. We propose an integrated hardware/software solution that automatically partition hardware resources between application and auxiliary threads. Each system level performs well-defined tasks efficiently: 1) the runtime system is enriched with a mechanism that automatically detects computing power requirements of running threads and drives the hardware actuators; 2) the hardware enforces dynamic resource partitioning; 3) the operating system provides an efficient interface between the runtime system and the hardware resource allocation mechanism. As a test case, we apply this adaptive approach to STM2, an software transactional memory system that implements the assisted execution model. We evaluate the proposed adaptive solution on an IBMPOWER7 system using Eigenbench and STAMP benchmark suite. Results show that our approach performs equal or better than the original STM2 and achieves up to 65% and 86% performance improvement for Eigenbench and STAMP applications, respectively.

Kestor, Gokcen↗