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The anisotropic Fourier Heat Conduction Equation (FHCE) and the multidimensional phonon Boltzmann Transport Equation (BTE) were solved numerically in cylindrical coordinates and in time domain to simulate a Time Domain Thermo-Reflectance (TDTR) experimental silicon/aluminum substrate/transducer setup. The out-of-phase response of the probe laser was predicted at various beam offset distances for a pump laser pulse frequency of 80 MHz and modulation frequency of 10 MHz and compared against experimental measurements for a silicon substrate. The isotropic FHCE was also solved for comparison. Results show that the isotropic FHCE with bulk thermal conductivity of 145 W/m/K significantly underpredicts the out-of-phase temperature difference, particularly at smaller beam offsets. With an isotropic thermal conductivity of 105 W/m/K, the computed results match experimental data at smaller beam offsets well, but overpredicts the experimental data at larger beam offsets. An almost-perfect match is obtained by using an anisotropic thermal conductivity wherein the radial (in-plane) thermal conductivity is set to 85 W/m/K and the axial (through-plane) conductivity is set to 130 W/m/K. The multidimensional frequency and polarization dependent phonon BTE is next solved. The BTE results for the out-of-phase temperature difference match experimental observations well at small and intermediate beam offsets, but overpredicts the experimental data at larger beam offsets. FHCE results are fitted to the BTE predictions, and the extracted (best fit) thermal conductivity is found to be 110 W/m/K. 

Heterogeneous computing environments combining CPU and GPU resources provide a great boost to large-scale scientific computing applications. Code generation utilities that partition the work into CPU and GPU tasks while considering data movement costs allow researchers to develop high-performance solutions more quickly and easily, and make these resources accessible to a larger user base.We present developments for a domain-specific language (DSL) and code generation framework for solving partial differential equations (PDEs). These enhancements facilitate GPU-accelerated solution of the Boltzmann transport equation (BTE) for phonons, which is the governing equation for simulating thermal transport in semiconductor materials at sub-micron scales. The solution of the BTE involves thousands of coupled PDEs as well as complicated boundary conditions and solving a nonlinear equation that couples all of the degrees of freedom at each time step. These developments enable the DSL to generate configurable hybrid GPU/CPU code that couples accelerated kernels with user-defined code. We observed performance improvements of around 18X compared to a CPU-only version produced by this same DSL with minimal additional programming effort. 

The Boltzmann Transport Equation (BTE) for phonons is often used to predict thermal transport at submicron scales in semiconductors. The BTE is a seven-dimensional nonlinear integro-differential equation, resulting in difficulty in its solution even after linearization under the single relaxation time approximation. Furthermore, parallelization and load balancing are challenging, given the high dimensionality and variability of the linear systems' conditioning. This work presents a 'synthetic' scalable parallelization method for solving the BTE on large-scale systems. The method includes cell-based parallelization, combined band+cell-based parallelization, and batching technique. The essential computational ingredient of cell-based parallelization is a sparse matrix-vector product (SpMV) that can be integrated with an existing linear algebra library like PETSc. The combined approach enhances the cell-based method by further parallelizing the band dimension to take advantage of low inter-band communication costs. For the batched approach, we developed a batched SpMV that enables multiple linear systems to be solved simultaneously, merging many MPI messages to reduce communication costs, thus maintaining scalability when the grain size becomes very small. We present numerical experiments to demonstrate our method's excellent speedups and scalability up to 16384 cores for a problem with 12.6 billion unknowns. 

Abstract The Boltzmann Transport equation (BTE) was solved numerically in cylindrical coordinates and in time domain to simulate a Frequency Domain Thermo-Reflectance (FDTR) experiment. First, a parallel phonon BTE solver that accounts for all phonon modes, frequencies, and polarizations was developed and tested. The solver employs the finite-volume method (FVM) for discretization of physical space, and the finite-angle method (FAM) for discretization of angular space. The solution was advanced in time using explicit time marching. The simulations were carried out in time domain and band-based parallelization of the BTE solver was implemented. The phase lag between the temperature averaged over the probed region of the transducer and the modulated laser pump signal was extracted for a pump laser modulation frequency ranging from 20–200 MHz. It was found that with the relaxation time scales used in the present study, the computed phase lag is underpredicted when compared to experimental data, especially at smaller modulation frequencies. The challenges in solving the BTE for such applications are highlighted. 

The phonon Boltzmann transport equation is a good model for heat transfer in nanometer scale structures such as semiconductor devices. Computational complexity is one of the main challenges in numerically solving this set of potentially thousands of nonlinearly coupled equations. Writing efficient code will involve careful optimization and choosing an effective parallelization strategy, requiring expertise in high performance computing, mathematical methods, and thermal physics. To address this challenge, we present the domain specific language and code generation software Finch. This language allows a domain scientist to enter the equations in a simple format, provide only basic mathematical functions used in the model, and generate efficient parallel code. Even very complex systems of equations such as phonon Boltzmann transport can be entered in a very simple, intuitive way. A feature of the framework is flexibility in numerical methods, computing environments, parallel strategies, and other aspects of the generated code. We demonstrate Finch on this problem using a variety of parallel strategies and model configurations to demonstrate the flexibility and ease of use. 

Abstract The Fourier and the hyperbolic heat conduction equations were solved numerically to simulate a frequency-domain thermoreflectance (FDTR) experiment. Numerical solutions enable isolation of pump and probe laser spot size effects and use of realistic boundary conditions. The equations were solved in time domain and the phase lag between the temperature of the transducer (averaged over the probe laser spot) and the modulated pump laser signal was computed for a modulation frequency range of 200 kHz–200 MHz. Numerical calculations showed that extracted values of the thermal conductivity are sensitive to both the pump and probe laser spot sizes, while analytical solutions (based on Hankel transform) cannot isolate the two effects. However, for the same effective (combined) spot size, the two solutions are found to be in excellent agreement. If the substrate (computational domain) is sufficiently large, the far-field boundary conditions were found to have no effect on the computed phase lag. The interface conductance between the transducer and the substrate was found to have some effect on the extracted thermal conductivity. The hyperbolic heat conduction equation yielded almost the same results as the Fourier heat conduction equation for the particular case studied. The numerically extracted thermal conductivity value (best fit) for the silicon substrate considered in this study was found to be about 82–108 W/m/K, depending on the pump and probe laser spot sizes used. 

Abstract The Fourier heat conduction and the hyperbolic heat conduction equations were solved numerically to simulate a frequency-domain thermoreflectance (FDTR) experimental setup. Numerical solutions enable use of realistic boundary conditions, such as convective cooling from the various surfaces of the substrate and transducer. The equations were solved in time domain and the phase lag between the temperature at the center of the transducer and the modulated pump laser signal were computed for a modulation frequency range of 200 kHz to 200 MHz. It was found that the numerical predictions fit the experimentally measured phase lag better than analytical frequency-domain solutions of the Fourier heat equation based on Hankel transforms. The effects of boundary conditions were investigated and it was found that if the substrate (computational domain) is sufficiently large, the far-field boundary conditions have no effect on the computed phase lag. The interface conductance between the transducer and the substrate was also treated as a parameter, and was found to have some effect on the predicted thermal conductivity, but only in certain regimes. The hyperbolic heat conduction equation yielded identical results as the Fourier heat conduction equation for the particular case studied. The thermal conductivity value (best fit) for the silicon substrate considered in this study was found to be 108 W/m/K, which is slightly different from previously reported values for the same experimental data.