Related papers: FEniCS-preCICE: Coupling FEniCS to other Simulatio…
The NIF Integrated Computer Control System (ICCS) application software uses a set of service frameworks that assures uniform behavior spanning the front-end processors (FEPs) and supervisor programs. This uniformity is visible both in the…
The Photonic hybRid EleCtromagnetic SolvEr (PRECISE) is a Matlab based library to model large and complex photonics integrated circuits. Each circuit is modularly described in terms of waveguide segments connected through multiport nodes.…
Although software and firmware co-simulation is gaining popularity, it is still not widely used in the FPGA designs. This work presents easy and structured approach for software and firmware co-simulation for bus centric designs. The…
Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems. However, CFD+ML algorithms require exchange of data, synchronization, and…
An accurate, physically-based, and differentiable model of soft robots can unlock downstream applications in optimal control. The Finite Element Method (FEM) is an expressive approach for modeling highly deformable structures such as…
In practice, training using federated learning can be orders of magnitude slower than standard centralized training. This severely limits the amount of experimentation and tuning that can be done, making it challenging to obtain good…
Embedding Convolutional Neural Network (CNN) into edge devices for inference is a very challenging task because such lightweight hardware is not born to handle this heavyweight software, which is the common overhead from the modern…
Existing logic-in-memory (LiM) research is limited to generating mappings and micro-operations. In this paper, we present~\emph{MemSPICE}, a novel framework that addresses this gap by automatically generating both the netlist and testbench…
Simulations of vehicle/track interaction (VTI) in switches and crossings (S\&C) require taking into account the complexity of their geometry. The VTI can be handled via a co-simulation process between a finite element (FE) model of the…
Contrastive language-image pre-training aligns the features of text-image pairs in a common latent space via distinct encoders for each modality. While this approach achieves impressive performance in several zero-shot tasks, it cannot…
As a mechanism for devices to update a global model without sharing data, federated learning bridges the tension between the need for data and respect for privacy. However, classic FL methods like Federated Averaging struggle with non-iid…
Robotic cutting of soft materials is critical for applications such as food processing, household automation, and surgical manipulation. As in other areas of robotics, simulators can facilitate controller verification, policy learning, and…
CaNS-Fizzy -- Fizzy for short -- is a GPU-accelerated numerical solver for massively-parallel Direct Numerical Simulations (DNS) of incompressible two-phase flows. A DNS enables direct access to all flow quantities, resolved in time and…
A key challenge in eXplainable Artificial Intelligence is the well-known tradeoff between the transparency of an algorithm (i.e., how easily a human can directly understand the algorithm, as opposed to receiving a post-hoc explanation), and…
We propose SimSC, a remarkably simple framework, to address the problem of semantic matching only based on the feature backbone. We discover that when fine-tuning ImageNet pre-trained backbone on the semantic matching task, L2 normalization…
In current electronic structure research endeavors such as warm dense matter or machine learning applications, efficient development necessitates non-monolithic software, providing an extendable and flexible interface. The open-source idea…
An open source two-dimensional (2D) thermal finite element (FE) model of the Directed Energy Deposition (DED) process is developed using the Python-based FEniCS framework. The model incrementally deposits material ahead of the laser focus…
The democratization of machine learning systems has made the process of fine-tuning accessible to practitioners, leading to a wide range of open-source models fine-tuned on specialized tasks and datasets. Recent work has proposed to merge…
The demand for energy-efficient and high performance embedded systems drives the evolution of new hardware architectures, including concepts like approximate computing. This paper presents a novel reconfigurable embedded platform named…
Many multiphysics simulations involve processes evolving on disparate time scales, posing a challenge for efficient coupling. A naive approach that synchronizes all processes using the smallest time scale wastes computational resources on…