Nested estimation involves estimating an expectation of a function of a conditional expectation and has many important applications in operations research and machine learning. Nested simulation is a classic approach to this estimation, and the convergence rate of the mean squared error (MSE) of nested simulation estimators is only of order [Formula: see text], where Γ is the simulation budget. To accelerate the convergence, in this paper, we establish a jackkniFe-bAsed neSted simulaTion (FAST) method for nested estimation, and a unified theoretical analysis for general functions in the nested estimation shows that the MSE of the proposed method converges at the faster rate of [Formula: see text] or even [Formula: see text]. We also provide an efficient algorithm that ensures the estimator’s MSE decays at its optimal rate in practice. In numerical experiments, we apply the proposed estimator in portfolio risk measurement and Bayesian experimental design in operations research and machine learning areas, respectively, and numerical results are consistent with the theory presented. History: Accepted by Bruno Tuffin, Area Editor for Simulation. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72031006, 72101260, and 72394375]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0118 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0118 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

High efficient video coding (HEVC) is a new video coding compression standard. HEVC adopts context-based adaptive binary arithmetic coding (CABAC) as the entropy coding scheme. In this paper, the overall architecture and efficiency of the main frequency are improved by the optimization of the input and output modules and the module optimization of the arithmetic coding CABAC hardware structure. In terms of input module optimization, four-level buffer input and residual coefficient transmission optimization are adopted; in terms of arithmetic coding module optimization, context model index pre-reading, pre-normalization look-up table and in-line serial stream output design are adopted so as to improve the overall efficiency of the architecture and the main frequency, reduce resource consumption, and achieve a high-frequency hardware architecture of the efficient coding pipeline. The combined results show that the pipeline can operate at 370MHz with 43.49K gates aiming at 90nm process. The processing rate and throughput can support real-time encoding of 1080P video under the general test conditions of the HEVC standard of 30 frames per second.