NPS: A Framework for Accurate Program Sampling Using Graph Neural Network

With the end of Moore's Law, there is a growing demand for rapid architectural innovations in modern processors, such as RISC-V custom extensions, to continue performance scaling. Program sampling is a crucial step in microprocessor design, as it selects representative simulation points for workload simulation. While SimPoint has been the de-facto approach for decades, its limited expressiveness with Basic Block Vector (BBV) requires time-consuming human tuning, often taking months, which impedes fast innovation and agile hardware development. This paper introduces Neural Program Sampling (NPS), a novel framework that learns execution embeddings using dynamic snapshots of a Graph Neural Network. NPS deploys AssemblyNet for embedding generation, leveraging an application's code structures and runtime states. AssemblyNet serves as NPS's graph model and neural architecture, capturing a program's behavior in aspects such as data computation, code path, and data flow. AssemblyNet is trained with a data prefetch task that predicts consecutive memory addresses. In the experiments, NPS outperforms SimPoint by up to 63%, reducing the average error by 38%. Additionally, NPS demonstrates strong robustness with increased accuracy, reducing the expensive accuracy tuning overhead. Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings

Memory power and performance optimizations for contemporary computer system design.

Memory power and performance optimizations for contemporary computer system design

A hydrodynamic model of loop seal with a fluidized standpipe for a circulating fluidized bed

Loop seals are among the most common non-mechanical valves used in circulating fluidized bed systems. In the present work, a fundamental study is conducted of a fluidized loop seal, which consists of a fluidized standpipe, a fluidized supply chamber, and a fluidized recycling chamber. Based on the principles of momentum, mass, and energy conservation, a hydrodynamic model for a loop seal is established, consisting of 13 equations. The effects of operating conditions such as the bottom aeration rate, total solid inventory, and fluidizing gas velocity in the riser on the solids flow rate and the performance of the loop seal are studied by a combination of model analysis and experiments. The experiments are carried out in a circulating fluidized bed with silica gel particles (Geldart group A). The model predictions show good agreement with the experimental data. (C) 2017 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.</p

Experimental Study and Numerical Simulation of Bubbling Fluidized Beds with Fine Particles in Two and Three Dimensions

The present study provides a deeply analysis of the flow behavior of bubbling fluidized beds with fine particles in two- (2D) and three-dimensional (3D) conditions, and computational fluid dynamics (CFD) simulations of agglomerates fluidization are carried out coupled with the modified agglomerate-force balance model, correspondingly. The experimental results indicate that the fluidized bed can be divided into bottom unfluidized, middle ascending fluidized, and upper descending back-mixing sections. The local solids volume fraction value ranges from 0.11 to 0.30, which depends on the interaction between bubble phase (epsilon(s) = 0-0.04) and emulsion phase (epsilon(s) = 0.26-0.30). The wall effect appears to be weakened, and the cohesive particles fluidize more uniformly in 3D fluidized beds. The simulations are in reasonable agreement with the experimental findings. However, at the top region of the bed the predicted solids holdup slightly deviates from experimental measurement. The vector plots of computed agglomerates velocity support the central and wall falling down-both sides rising up flow pattern of solids, two core-annular flows exist in the bed, which can be also observed experimentally

Fluidization characteristics of aerogel Co/Al2O3 catalyst in a magnetic fluidized bed and its application to CH4-CO2 reforming

The fluidization characteristics of a nanoparticle catalyst were investigated in a fluidized bed assisted with an axial magnetic field. It showed that slugging and channeling, commonly observed when processing nanoparticles via conventional fluidized bed reactors, could be effectively eliminated, and the size of the agglomerates and bubble diameter could also be reduced with the aid of the magnetic field, leading to much improved gas–solid contact efficiency. Due to the improved gas–solid contact efficiency, the performance of the CH4–CO2 catalytic reforming has been significantly enhanced, where the initial conversion of CH4 was 7.6% and 24.3% higher than those obtained in a conventional fluidized bed reactor and a fixed bed reactor. The catalytic deactivation, caused by carbon deposition on catalyst surfaces, is also slower in the magnetic fluidized bed operation, where the CH4 conversion is 11.7% and 42.6% greater as compared with those in the conventional fluidized bed operation and the fixed bed operation. The present investigations demonstrated that carbon deposition can be much suppressed through improving the gas–solid contact efficiency with the assistance of the magnetic field

Simulation with a structure-based mass-transfer model for turbulent fluidized beds

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Simulation with a structure-based mass-transfer model for turbulent fluidized beds

A structure-based mass-transfer model for turbulent fluidized beds (TFBs) was established according to mass conservation and the balance of mass transfer and reaction. Unlike the traditional method, which assumes a homogeneous structure, this model considered the presence of voids and particle clusters in TFBs and built correlations for each phase. The flow parameters were solved based on a previously proposed structure-based drag model. The catalytic combustion of methane at three temperatures and ozone decomposition at various gas velocities were used to validate the model. The TFB reactions comprised intrinsic reaction kinetics, internal diffusion, and external diffusion. The simulation results, which compared favorably with experimental data and were better than those based on the average method, demonstrated that methane was primarily consumed at the bottom of the bed and the methane concentration was closely related to the presence of the catalyst. The flow and diffusion had an important effect on the methane concentration. This model also predicted the outlet concentrations for ozone decomposition, which increased with increasing gas velocity. Interphase mass transfer was presented as the limiting step for this system. This structure-based mass-transfer model is important for the industrial application of TFBs. (C) 2017 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved