From 6b5941848eb600d348b0f6749a2923dd8abc2c40 Mon Sep 17 00:00:00 2001 From: Mehdi Ataei Date: Tue, 19 Mar 2024 16:12:38 -0400 Subject: [PATCH 1/3] Update README.md --- README.md | 43 ++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 42 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 6bb7727..91f5cdc 100644 --- a/README.md +++ b/README.md @@ -153,4 +153,45 @@ git clone https://github.com/Autodesk/XLB cd XLB export PYTHONPATH=. python3 examples/CFD/cavity2d.py -``` \ No newline at end of file +``` +## Roadmap + +### Work in Progress (WIP) +*Note: Some of the work-in-progress features can be found in the branches of the XLB repository. For contributions to these features, please reach out.* + +🚀 **Warp Backend:** Achieving state-of-the-art performance by leveraging the [Warp](https://github.com/NVIDIA/warp) framework in combination with JAX. + +🌐 **Grid Refinement:** Implementing adaptive mesh refinement techniques for enhanced simulation accuracy. + +⚡ **Multi-GPU Acceleration using [Neon](https://github.com/Autodesk/Neon) + Warp:** Using Neon's data structure for better overlapping computation and communication. + +💾 **Out-of-Core Computations:** Enabling simulations that exceed available GPU memory, suitable for CPU+GPU coherent memory models such as NVIDIA's Grace Superchips. + +🗜ī¸ **GPU Accelerated Lossless Compression and Decompression**: Implementing high-performance lossless compression and decompression techniques for larger-scale simulations and improved performance. + +🌡ī¸ **Fluid-Thermal Simulation Capabilities:** Incorporating heat transfer and thermal effects into fluid simulations. + +đŸŽ¯ **Adjoint-based Shape and Topology Optimization:** Implementing gradient-based optimization techniques for design optimization. + +🧠 **Machine Learning Accelerated Simulations:** Leveraging machine learning to speed up simulations and improve accuracy. + +📉 **Reduced Order Modeling using Machine Learning:** Developing data-driven reduced-order models for efficient simulations. + + +### Wishlist +*Contributions to these features are welcome. Please submit PRs for the Wishlist items.* + +🌊 **Free Surface Flows:** Simulating flows with free surfaces, such as water waves and droplets. + +📡 **Electromagnetic Wave Propagation:** Simulating the propagation of electromagnetic waves. + +🛩ī¸ **Supersonic Flows:** Simulating supersonic flows based on the techniques described in [this paper](https://royalsocietypublishing.org/doi/10.1098/rsta.2019.0559). + +🤝 **Fluid-Solid Interaction (Using Immersed Boundary Method):** Modeling the interaction between fluids and solid objects. + +🧩 **Multiphase Flow Simulation:** Simulating flows with multiple immiscible fluids. + +đŸĒ¨ **Particle Flows and Discrete Element Method:** Incorporating particle-based methods for granular and particulate flows. + +🔧 **Better Geometry Processing Pipelines:** Improving the handling and preprocessing of complex geometries for simulations. + From 574dd7ff414a9ceb389ef5177ddc999226604b89 Mon Sep 17 00:00:00 2001 From: Mehdi Ataei Date: Tue, 19 Mar 2024 16:20:42 -0400 Subject: [PATCH 2/3] Update README.md --- README.md | 34 ++++++++++++++++++---------------- 1 file changed, 18 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index 91f5cdc..aad6134 100644 --- a/README.md +++ b/README.md @@ -159,39 +159,41 @@ python3 examples/CFD/cavity2d.py ### Work in Progress (WIP) *Note: Some of the work-in-progress features can be found in the branches of the XLB repository. For contributions to these features, please reach out.* -🚀 **Warp Backend:** Achieving state-of-the-art performance by leveraging the [Warp](https://github.com/NVIDIA/warp) framework in combination with JAX. +- 🚀 **Warp Backend:** Achieving state-of-the-art performance by leveraging the [Warp](https://github.com/NVIDIA/warp) framework in combination with JAX. -🌐 **Grid Refinement:** Implementing adaptive mesh refinement techniques for enhanced simulation accuracy. + - 🌐 **Grid Refinement:** Implementing adaptive mesh refinement techniques for enhanced simulation accuracy. -⚡ **Multi-GPU Acceleration using [Neon](https://github.com/Autodesk/Neon) + Warp:** Using Neon's data structure for better overlapping computation and communication. +- ⚡ **Multi-GPU Acceleration using [Neon](https://github.com/Autodesk/Neon) + Warp:** Using Neon's data structure for improved scaling. -💾 **Out-of-Core Computations:** Enabling simulations that exceed available GPU memory, suitable for CPU+GPU coherent memory models such as NVIDIA's Grace Superchips. +- 💾 **Out-of-Core Computations:** Enabling simulations that exceed available GPU memory, suitable for CPU+GPU coherent memory models such as NVIDIA's Grace Superchips. -🗜ī¸ **GPU Accelerated Lossless Compression and Decompression**: Implementing high-performance lossless compression and decompression techniques for larger-scale simulations and improved performance. +- 🗜ī¸ **GPU Accelerated Lossless Compression and Decompression**: Implementing high-performance lossless compression and decompression techniques for larger-scale simulations and improved performance. -🌡ī¸ **Fluid-Thermal Simulation Capabilities:** Incorporating heat transfer and thermal effects into fluid simulations. +- 🌡ī¸ **Fluid-Thermal Simulation Capabilities:** Incorporating heat transfer and thermal effects into fluid simulations. -đŸŽ¯ **Adjoint-based Shape and Topology Optimization:** Implementing gradient-based optimization techniques for design optimization. +- đŸŽ¯ **Adjoint-based Shape and Topology Optimization:** Implementing gradient-based optimization techniques for design optimization. -🧠 **Machine Learning Accelerated Simulations:** Leveraging machine learning to speed up simulations and improve accuracy. +- 🧠 **Machine Learning Accelerated Simulations:** Leveraging machine learning to speed up simulations and improve accuracy. -📉 **Reduced Order Modeling using Machine Learning:** Developing data-driven reduced-order models for efficient simulations. +- 📉 **Reduced Order Modeling using Machine Learning:** Developing data-driven reduced-order models for efficient and accurate simulations. ### Wishlist *Contributions to these features are welcome. Please submit PRs for the Wishlist items.* -🌊 **Free Surface Flows:** Simulating flows with free surfaces, such as water waves and droplets. +- 🌊 **Free Surface Flows:** Simulating flows with free surfaces, such as water waves and droplets. -📡 **Electromagnetic Wave Propagation:** Simulating the propagation of electromagnetic waves. +- 📡 **Electromagnetic Wave Propagation:** Simulating the propagation of electromagnetic waves. -🛩ī¸ **Supersonic Flows:** Simulating supersonic flows based on the techniques described in [this paper](https://royalsocietypublishing.org/doi/10.1098/rsta.2019.0559). +- 🛩ī¸ **Supersonic Flows:** Simulating supersonic flows. -🤝 **Fluid-Solid Interaction (Using Immersed Boundary Method):** Modeling the interaction between fluids and solid objects. +- 🌊🧱 **Fluid-Solid Interaction:** Modeling the interaction between fluids and solid objects. -🧩 **Multiphase Flow Simulation:** Simulating flows with multiple immiscible fluids. +- 🧩 **Multiphase Flow Simulation:** Simulating flows with multiple immiscible fluids. -đŸĒ¨ **Particle Flows and Discrete Element Method:** Incorporating particle-based methods for granular and particulate flows. +- đŸ”Ĩ **Combustion:** Simulating combustion processes and reactive flows. -🔧 **Better Geometry Processing Pipelines:** Improving the handling and preprocessing of complex geometries for simulations. +- đŸĒ¨ **Particle Flows and Discrete Element Method:** Incorporating particle-based methods for granular and particulate flows. + +- 🔧 **Better Geometry Processing Pipelines:** Improving the handling and preprocessing of complex geometries for simulations. From e351e49a07b3695544985c75d90fd690e9999a29 Mon Sep 17 00:00:00 2001 From: Mehdi Ataei Date: Tue, 4 Jun 2024 08:48:21 +0100 Subject: [PATCH 3/3] Updated paper link/citation to CPC --- README.md | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index aad6134..dcb67ee 100644 --- a/README.md +++ b/README.md @@ -10,18 +10,21 @@ XLB is a fully differentiable 2D/3D Lattice Boltzmann Method (LBM) library that ## Accompanying Paper -Please refer to the [accompanying paper](https://arxiv.org/abs/2311.16080) for benchmarks, validation, and more details about the library. +Please refer to the [accompanying paper](https://doi.org/10.1016/j.cpc.2024.109187) for benchmarks, validation, and more details about the library. ## Citing XLB If you use XLB in your research, please cite the following paper: ``` -@article{ataei2023xlb, - title={{XLB}: A Differentiable Massively Parallel Lattice Boltzmann Library in Python}, - author={Ataei, Mohammadmehdi and Salehipour, Hesam}, - journal={arXiv preprint arXiv:2311.16080}, - year={2023}, +@article{ataei2024xlb, + title={{XLB}: A differentiable massively parallel lattice {Boltzmann} library in {Python}}, + author={Ataei, Mohammadmehdi and Salehipour, Hesam}, + journal={Computer Physics Communications}, + volume={300}, + pages={109187}, + year={2024}, + publisher={Elsevier} } ```