hello, Ruochun. Thank you for your advice, now I am trying to prepare the
dataset, and everything seems good now!
Then, I have a question about the unit in the *demo_GPU_ballcosim.json*. In
this json, the unit of "sphere_radius"、"box_X" seems to be *mm*, but the
"grav_Z" equals -980, so I guess it's *cm/s^2* ?
The reason why I want to know is because the force I measured is over 1e8,
so I guess its unit is not N?
I noticed that the chrono system should not have uniform unit, but all
units need to correspond. I would appreciate it very much if you could tell
me the units of the "normalStiffS2S"、normalDampS2S" in this by the way.
*demo_GPU_ballcosim.json*
{
"sphere_radius": 1,
"sphere_density": 1,
"box_X": 300,
"box_Y": 300,
"box_Z": 200,
"step_size": 5e-5
"time_end": 2,
"grav_X": 0,
"grav_Y": 0,
"grav_Z": -980,
"normalStiffS2S": 1e8,
"normalStiffS2W": 1e8,
"normalStiffS2M": 1e8,
"normalDampS2S": 10000,
"normalDampS2W": 10000,
"normalDampS2M": 10000,
"tangentStiffS2S": 1e8,
"tangentStiffS2W": 1e8,
"tangentStiffS2M": 1e8,
"tangentDampS2S": 2000,
"tangentDampS2W": 2000,
"tangentDampS2M": 2000,
"static_friction_coeffS2S": 0.5,
"static_friction_coeffS2W": 0.5,
"static_friction_coeffS2M": 0.5,
"cohesion_ratio": 0,
"adhesion_ratio_s2w": 0,
"adhesion_ratio_s2m": 0,
"verbose": 0,
"run_mode": 1,
"psi_T": 32,
"psi_L": 16,
"output_dir": "ballcosim",
"write_mode": "csv"
}
在2022年11月25日星期五 UTC+8 06:33:36<Ruochun Zhang> 写道：
> Hi,
>
> In terms of involving simulation results of Chrono::GPU in your
> reinforcement learning project, I would suggest you generate the dataset
> using Chrono::GPU, and then use the dataset in the training. You probably
> have to do that anyway, even if Chrono's DEM support is wrapped in Python.
>
> Ruochun
>
> On Thursday, November 24, 2022 at 8:23:18 AM UTC-6 Radu Serban wrote:
>
>> You are correct: Chrono::GPU is currently not wrapped in PyChrono.
>>
>> But you can certainly use smooth contact (that is construct a
>> ChSystemSMC) in PyChrono. Where/what did you see that made you think that’s
>> not possible?
>>
>>
>>
>> --Radu
>>
>>
>>
>> *From:* 'yibing Yan' via ProjectChrono <[email protected]>
>> *Sent:* Thursday, 24 November 2022 13:37
>> *To:* ProjectChrono <[email protected]>
>> *Subject:* [chrono] Re: the GPU module and the multicore module
>>
>>
>>
>>
>> Hi,
>>
>>
>>
>> Thank you for your advice, after trying for several days, I succeed in
>> using co-simulation, and it took only 10 minutes every one simulation. I
>> have another question now, as I said before, I am going to use
>> reinforcement learning with chrono. I think of using openAI and I also
>> found projectchrono <https://github.com/projectchrono>/*gym-chrono
>> <https://github.com/projectchrono/gym-chrono>*. However, I don't know if
>> I can realize what I have done with *PyChrono*, because the
>> Chrono::Engine Python module does not cover all the features of the C++ API.
>>
>> Meanwhile, in Project Chrono: Install the PYTHON module
>> <https://api.projectchrono.org/development/module_python_installation.html>,
>>
>> I found maybe I can't use Chrono::GPU system and Chrono SMC system in
>> PyChrono. Can you give me any advice?
>>
>> Thank you very much again sincerely!
>>
>> 在2022年11月11日星期五 UTC+8 11:29:20<Ruochun Zhang> 写道：
>>
>> Hi,
>>
>>
>>
>> What you wanted is possible. There is no problem creating two systems in
>> one script, the only problem is their interaction. You can do that via
>> co-simulation. Like a said, *demo_GPU_ballcosim *may give you an idea on
>> how to do that. The general idea is that your complex mechanical system
>> involving ChBodies and joints and such, will still be managed by a Chrono
>> SMC system. Those ChBodies can be instructed to receive external forces and
>> torques via accumulators; those external forces and torques in this case
>> should be queried from Chrono::GPU simulations. That is, you load obj
>> meshes into a Chrono::GPU system, and in each time step, you let it compute
>> the contact forces between meshes and particles, then feed that information
>> to ChBodies to update the locations of those bodies, then feed the new
>> locations of these obj meshes back to Chrono::GPU to complete one time
>> step, and then repeat.
>>
>>
>>
>> If your particle system is large I wouldn't recommend doing runtime
>> visualization anyway, that'd be totally prohibiting in terms of
>> computational cost. Chrono::GPU can write particles and meshes to files,
>> and maybe you should generate movies based on those as a post-processing
>> step.
>>
>>
>>
>> Thank you,
>>
>> Ruochun
>>
>>
>>
>> On Thursday, November 10, 2022 at 6:41:44 AM UTC-6 [email protected] wrote:
>>
>> Hi, thank you for your response!
>>
>> First of all, I may have to apologise for my language skills and I really
>> appreciate that you are willing to listen to my ideas. I'd like to describe
>> my question again. I have finished a complete complex experiment, including
>> around 10k granular objects, two objs of my own, one container by using
>> *utils::AddBoxGeometry* and several links and motors, such as
>> *ChLinkMotorRotationSpeed*、*ChLinkMotorLinearSpeed*、*ChLinkMateFix*. I
>> achieved it by using *the MCORE module*, although it can speed up the
>> program by using multiple threads, it still took 2 hours four one time
>> simulation.
>>
>>
>>
>> Now I am considering using the reinforcement learning afterwards, so it
>> is important to improve the simulation speed. I am wondering if I can use
>> *Chrono::GPU* only for my granular objects, and all other content
>> remains the same by using *the MCORE module.* More specifically, I plan
>> to use both *ChSystemMulticoreSMC* and *ChSystemGpuMesh* in one cpp. The
>> reason I want to do this is because *Chrono::GPU* is more like a
>> separate module, some of the functions I need for simulation can't be found
>> in *Chrono::GPU*, but can be found in *the MCORE module* and are already
>> realized through my previous efforts.
>>
>>
>>
>> I also note that *Chrono::GPU *quote ChronoEngine_GPU、
>> ChronoEngine_irrlicht、ChronoEngine_multicore、ChronoEngine_opengl、
>> ChronoEngine_postprocess、ChronoEngine_robot and *ChronoEngine_multicore(*
>> *the MCORE module* *) *is the one which I used now. So I can use
>> MCORE-functions in cpps in *Chrono::GPU*，by including the .h insteading
>> of modify the CMakeLists.txt.
>>
>>
>>
>> I tried and felt if this idea was unattainable. Because I need to create
>> two systems in one cpp. Meanwhile, for visualization,
>> *opengl::ChVisualSystemOpenGL* is used in *the* *MCORE module *and
>> *ChGpuVisualization* is used in *the Chrono::GPU *and I can't find an
>> interface between the two which means they can't be showed in one window. I
>> don't know how to solve this problem anymore and I wonder if you have any
>> suggestions.
>>
>>
>>
>> I really appreciate your help!
>>
>>
>>
>>
>>
>>
>>
>> 在2022年11月10日星期四 UTC+8 13:29:20<Ruochun Zhang> 写道：
>>
>> Hi,
>>
>>
>>
>> I hope someone can provide better help on the linkage issue. What I can
>> say is that you can try building it with cuda11.6 and the newest gcc. If
>> you are using cuda11.8, or an ancient version of cuda or gcc, I cannot be
>> sure. I've been building it with the said configuration with no problem, on
>> Linux or Windows.
>>
>>
>>
>> About Chrono::GPU's usage, yes it supports obj meshes. I am not sure
>> about what you meant by multi-core acceleration. I might, if you elaborate
>> a bit. And Chrono::GPU should interact with Chrono just fine, for that
>> maybe you can have a look at the *ballcosim *demo.
>>
>>
>>
>> If you care about polydisperse spherical particles or complex shaped
>> particles, then DEM-Engine is the way to go. You can start using it now.
>> Indeed, documentations are being added. I can drop you a message when it
>> becomes more accessible. Right now, I attached a snippet from one of my
>> previous emails, to help you understand how to build this tool on Linux. In
>> terms of using it, I'd start with checking out and running its demos. And
>> then, the methods in *API.h* are mostly commented, which for now, may
>> serve as an ad-hoc documentation for you to understand what some of its
>> basic usages are.
>>
>> Thank you,
>>
>> Ruochun
>>
>> On Wednesday, November 9, 2022 at 2:19:40 AM UTC-6 [email protected] wrote:
>>
>> Hi, thank you very much for your help!
>>
>> After last mail, I choosed to use the multicore, the simulation took 2
>> hours every time now, because I was constantly adding requests and
>> features and the number of bodies comes to 10k. Meanwhile, I bought a 3080
>> and a new computer. I am considering using the reinforcement learning
>> afterwards, so it is important to improve the simulation speed.
>>
>> I have studied your response several times，I am wondering if I can only
>> use Chrono::GPU for my particle-related content, and all other content
>> remains the same, such as multi-core acceleration, loading my own obj. More
>> specifically, I plan to use both ChSystemMulticoreSMC and ChSystemGpuMesh.
>> When compile the project, there are errors "LNK2019：Unresolvable
>> external symbols" in every functions defined in GPU and used in the
>> Muticore and I feel this is a deeper issue involving linkers. So I would
>> like to ask for guidance or is there another way to use the Chrono::GPU as
>> a DEMsolver only for the particles.
>>
>> And I learned something about projectchrono
>> <https://github.com/projectchrono>/*DEM-Engine*
>> <https://github.com/projectchrono/DEM-Engine>, but I found how to
>> Install DEM-Engine and the DEM-Engine usage are still waiting to be
>> added, I would love to try it if I could.
>>
>> Thank you again!
>>
>>
>>
>> 在2022年9月24日星期六 UTC+8 14:45:22<Ruochun Zhang> 写道：
>>
>> Hi,
>>
>>
>>
>> The GPU module does benefit a lot from more recent hardware. If your test
>> case does not feature a huge number of bodies, say some 10k, then multicore
>> can be a good choice. It probably requires less learning from you too.
>>
>>
>>
>> It should be noted that Chrono::GPU is not "Chrono on GPU". Most Chrono
>> core classes and methods cannot be used in Chrono::GPU. For all
>> purposes, Chrono::GPU can be seen as a standalone DEM solver for
>> monodisperse spherical particles, implemented on GPU. It should be used to
>> simulate granular materials, and it can interact with Chrono (core) so that
>> it becomes possible to bring a small number of more complex objects (such
>> as your spoon) into the simulation as well. So if you would like to use
>> Chrono::GPU, you have to start from its demos, to learn how to use its own
>> methods to instantiate and manage granular particles. Chrono::GPU's main
>> advantage is being fast. If your simulation has to involve millions of
>> granular particles, then multicore will not do and GPU is the choice.
>>
>>
>>
>> More specifically, *CreateCylindricalContainerFromBoxes* is not a
>> Chrono::GPU thing at all. *cohesion_ratio* is about the cohesion between
>> Chrono::GPU particles, and it has nothing to do with gravity, which is set
>> by *SetGravitationalAcceleration* in Chrono::GPU.
>>
>>
>>
>> On a different note, Chrono's DEM/granular support on GPU is moving
>> towards a new direction. The support for complex granular particle shapes
>> will be added and it will become a duo-GPU solver. It will be based on
>> SBEL's
>> new DEM Engine <https://github.com/uwsbel/DEM-Engine>. Apart from being
>> more general and having higher efficiency, the usage of it is similar to
>> Chrono::GPU, as a standalone helper to Chrono core which manages the
>> granular part of the simulation, or work on its own as a dedicated DEM
>> solver. If from the previous conversation you believe Chrono::GPU is for
>> you, then likely this package will be of interest. More documentations and
>> user guides are being added to it. But again, it does benefit from recent
>> GPUs though.
>>
>>
>>
>> Thank you,
>>
>> Ruochun
>>
>>
>>
>> On Sunday, September 18, 2022 at 2:13:24 AM UTC-5 [email protected] wrote:
>>
>> hello there,
>>
>> I am tring to perform a simulation which I want to put an object like a
>> spoon and scoop the sand(granular objects) to see the force in the process.
>>
>> I find that demo_GPU_mixer.cpp demo can be referenced, but I am not sure
>> whether I need to add a container holding those sand and give the granular
>> objects gravity. If this is so, should I use
>> *CreateCylindricalContainerFromBoxes* to add container and use
>> *cohesion_ratio* in the .json to add the gravity? Also, I am sad that I
>> have a poor GPU so that it really take a long long time to run the gpu
>> module.
>>
>> Then I find that there are also some granular objects demos in the
>> multicore module, I find some demos about a container with granular
>> material. And I can run those demos faster.
>>
>> Now I am confused about what thing to do next is much better.
>>
>>
>>
>> Any help will be appreciated, thank you so much in advance.
>>
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