`hotwheels` is a code for hydrodynamic N-body cosmological simulations, `hotwheels` components are made of **C low-level kernels driven by python wrappers**.
`hotwheels` is a code for hydrodynamic N-body cosmological simulations, `hotwheels` components are made of **C low-level kernels driven by python wrappers**.
`hotwheels` is developed by **Antonio Ragagnin**. And, as part of my commitment to advancing simulation tools, I am working on a flexible and modular implementation of a [Gadget](https://wwwmpa.mpa-garching.mpg.de/gadget/)-like code (temporarily named `hotwheels`). This new implementation incorporates lessons learned from over a decade of experience working with HPC and Gadget codes (e.g., OpenGadget3, see Dolag et al., in prep).
`hotwheels` is developed by **Antonio Ragagnin**. And, as part of my commitment to advancing simulation tools, I am working on a flexible and modular implementation of a [Gadget](https://wwwmpa.mpa-garching.mpg.de/gadget/)-like code (temporarily named `hotwheels`).
This new implementation incorporates lessons learned from over a decade of experience working with HPC and Gadget codes,
for instance see my greentree in [Ragagnin et al. (2017)](https://ebooks.iospress.nl/publication/42679),
my GPU scheme for N-body codes as in [Ragagnin et al. (2020)](https://ebooks.iospress.nl/publication/53922)(and Ragagnin et al., 2025, in review),
my parallel tree build tests (fund by HPC Europa3, ID HPC17YMAKH), and other unpublished activities
in the context of OpenGadget3 (PI. Klaus Dolag).
`hotwheels` is designed to leverage CPU and GPU parallelism, with a strong emphasis on modularity. This modular approach facilitates collaboration with HPC engineers and GPU vendors, enabling efficient utilization of HPC systems. Modularity also enhances testability, simplifies the addition of new features, and allows rethinking code structure based on past experiences.
`hotwheels` is designed to leverage CPU and GPU parallelism, with a strong emphasis on modularity. This modular approach facilitates collaboration with HPC engineers and GPU vendors, enabling efficient utilization of HPC systems. Modularity also enhances testability, simplifies the addition of new features, and allows rethinking code structure based on past experiences.
