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Xing Cai

Professor

University of Oslo

Norway

Research Interests

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Professors in Norway Professors in Cell Biology Cell Biology professors in Norway

About

Professor Xing Cai is a faculty member at the University of Oslo, Norway. His research primarily focuses on computational methods in physics and engineering, with recent works highlighting automated parameter tuning, GPU-accelerated finite element computations, and detailed modeling of cardiac mechanics. He is actively engaged in investigating performance optimizations in reservoir simulations and multi-core CPU architectures.

Articles (17)

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2026

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2022

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2021

Collaborators (4)

Pascal Bouvry

Dean

University of Luxembourg

LUXEMBOURG

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Ira Assent

VIP, Professor

Aarhus University

DENMARK

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Samuel Wall

Simula Research Laboratory

NORWAY

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Joakim Sundnes

Research Scientist/Research Director

Simula Research Laboratory

NORWAY

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Xing Cai

Research Interests

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About

Articles (17)

Performance evaluation of the OpenACC API targeting multi-GPU data transfers: A case study of porting parallel 3D sweeping algorithms for geological folding

A control-theoretic approach to adaptive time stepping in reservoir simulations and its impacts on efficiency and robustness

Geld: Load-balanced D-Core Decomposition for Consumer GPUs

CAC: An asynchronous non-blocking consistency model with bounded staleness for distributed machine learning

Performance and Programmability of MPI+X Integration with CUDA, HIP, SYCL, OpenACC, and OpenMP Offloading for Supercomputing: A Case Study on Dense Matrix–Vector Multiplication

CPU- and GPU-initiated Communication Strategies for Conjugate Gradient Methods on Large GPU Clusters

Modelling Load Imbalance In Shared Memory Multicore Systems

Automated parameter tuning with accuracy control for efficient reservoir simulations

Editorial: Heterogeneous computing in physics-based models

Targeting performance and user-friendliness: GPU-accelerated finite element computation with automated code generation in FEniCS

Detailed Modeling of Heterogeneous and Contention-Constrained Point-to-Point MPI Communication

A cell-based framework for modeling cardiac mechanics

Enabling unstructured-mesh computation on massively tiled AI processors: An example of accelerating in silico cardiac simulation

On Memory Traffic and Optimisations for Low-order Finite Element Assembly Algorithms on Multi-core CPUs

Resource-Efficient Use of Modern Processor Architectures For Numerically Solving Cardiac Ionic Cell Models

On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations

Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells

Collaborators (4)

Pascal Bouvry

Ira Assent

Samuel Wall

Joakim Sundnes

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