An official website of the United States government
The microservice architecture style has gained popularity due to its ability to fault isolation, ease of scaling applications, and developer’s agility. However, writing applications in the microservice design style has its challenges. Due to the loosely coupled nature, services communicate with others through standard communication APIs. This incurs significant overhead in the application due to communication protocol and data transformation. An inefficient service communication at the microservice application logic can further overwhelm the application. We perform a grey literature review showing that unnecessary data transfer is a real challenge in the industry. To the best of our knowledge, no effective tool is currently available to accurately identify the origins of unnecessary microservice communications that lead to significant performance overhead and provide guidance for optimization. To bridge the knowledge gap, we propose MicroProf, a dynamic program analysis tool to detect unnecessary data transfer in Java-based microservice applications. At the implementation level, MicroProfproposes novel techniques such as remote object sampling and hardware debug registers to monitor remote object usage. MicroProfreports the unnecessary data transfer at the application source code level. Furthermore, MicroProfpinpoints the opportunities for communication API optimization. MicroProfis evaluated on four well-known applications involving two real-world applications and two benchmarks, identifying five inefficient remote invocations. Guided by MicroProf, API optimization achieves an 87.5% reduction in the number of fields within REST API responses. The empirical evaluation further reveals that the optimized services experience a speedup of up to 4.59 ×.
more »
« less
Quantitative analysis of zero-field splitting parameter distributions in Gd( iii ) complexes
The Zero-Field Splitting (ZFS) distributions in Gd(iii) centers are accurately analyzed, with detailed discussion of error bars, and compared to the calculations with superposition model.
more »
« less
- Award ID(s):
- 1617025
- PAR ID:
- 10056029
- Publisher / Repository:
- Royal Society of Chemistry (RSC)
- Date Published:
- Journal Name:
- Physical Chemistry Chemical Physics
- Volume:
- 20
- Issue:
- 15
- ISSN:
- 1463-9076
- Page Range / eLocation ID:
- 10470 to 10492
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The rapid advancement of large-scale cosmological simulations has opened new avenues for cosmological and astrophysical research. However, the increasing diversity among cosmological simulation models presents a challenge to therobustness. In this work, we develop the Model-Insensitive ESTimator (Miest), a machine that canrobustlyestimate the cosmological parameters, Ωmandσ8, from neural hydrogen maps of simulation models in the Cosmology and Astrophysics with MachinE Learning Simulations project—IllustrisTNG,SIMBA, Astrid, and SWIFT-Eagle. An estimator is consideredrobustif it possesses a consistent predictive power across all simulations, including those used during the training phase. We train our machine using multiple simulation models and ensure that it only extracts common features between the models while disregarding the model-specific features. This allows us to develop a novel model that is capable of accurately estimating parameters across a range of simulation models, without being biased toward any particular model. Upon the investigation of the latent space—a set of summary statistics, we find that the implementation ofrobustnessleads to the blending of latent variables across different models, demonstrating the removal of model-specific features. In comparison to a standard machine lackingrobustness, the average performance of Mieston the unseen simulations during the training phase has been improved by ∼17% for Ωmand 38% forσ8. By using a machine learning approach that can extractrobust, yet physical features, we hope to improve our understanding of galaxy formation and evolution in a (subgrid) model-insensitive manner, and ultimately, gain insight into the underlying physical processes responsible forrobustness.more » « less
-
Abstract A fundamental understanding of the enantiospecific interactions between chiral adsorbates and understanding of their interactions with chiral surfaces is key to unlocking the origins of enantiospecific surface chemistry. Herein, the adsorption and decomposition of the amino acid proline (Pro) have been studied on the achiral Cu(110) and Cu(111) surfaces and on the chiral Cu(643)R&Ssurfaces. Isotopically labelled 1‐13C‐l‐Pro has been used to probe the Pro decomposition mechanism and to allow mass spectrometric discrimination ofd‐Pro and 1‐13C‐l‐Pro when adsorbed as mixtures. On the Cu(111) surface, X‐ray photoelectron spectroscopy reveals that Pro adsorbs as an anionic species in the monolayer. On the chiral Cu(643)R&Ssurface, adsorbed Pro enantiomers decompose with non‐enantiospecific kinetics. However, the decomposition kinetics were found to be different on the terraces versus the kinked steps. Exposure of the chiral Cu(643)R&Ssurfaces to a racemic gas phase mixture ofd‐Pro and 1‐13C‐l‐Pro resulted in the adsorption of a racemic mixture; i.e., adsorption is not enantiospecific. However, exposure to non‐racemic mixtures ofd‐Pro and 1‐13C‐l‐Pro resulted in amplification of enantiomeric excess on the surface, indicative of homochiral aggregation of adsorbed Pro. During co‐adsorption, this amplification is observed even at very low coverages, quite distinct from the behavior of other amino acids, which begin to exhibit homochiral aggregation only after reaching monolayer coverages. The equilibrium adsorption ofd‐Pro and 1‐13C‐l‐Pro mixtures on achiral Cu(110) did not display any aggregation, consistent with prior scanning tunneling microscopy (STM) observations ofdl‐Pro/Cu(110). This demonstrates convergence between findings from equilibrium adsorption methods and STM experiments and corroborates formation of a 2D random solid solution.more » « less
