ParticleLib | Multiversion spigot library supporting all particles | Plugin library
kandi X-RAY | ParticleLib Summary
kandi X-RAY | ParticleLib Summary
Multiversion spigot library supporting all particles and their data (1.8-1.18)
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Top functions reviewed by kandi - BETA
- Creates a new VibrationPart instance
- Create a new BlockPosition object
- Returns the current effect
- Gets the entity handle
- Send a collection of ProicleBuilders
- Send a collection of ParticleBuilders
- Send a collection of ProicleBuilders to the players
- Sets the offset of the particle
- Sets the offset of the particle
- Returns the mapped class
- Gets the input stream for a resource
- Creates a SculkChargeOptions instance
- Creates a new ShriekPart instance
- Checks if a class exists
- Set the plugin to use
- Returns the constructor without throwing an exception
- Gets the singleton player with the specified target player
- Gets the mapped field
- Sets the color of the particle
- Returns the mapped method for the given name and parameter types
- Process a mapping
- Returns the nms particle data
- Returns the nms data of this particle
- Creates a new NMS object
- Returns the NMSData object
- Convert the object to the NMS data
ParticleLib Key Features
ParticleLib Examples and Code Snippets
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Trending Discussions on ParticleLib
QUESTION
im working on a fluid simulator using opengl (implementing the sph algorithm). I've tried many methods to run my simulator, first i used octrees, after that hashmaps and now i am trying to use Z order, and for that i need to order my particles based on their index.
What i am having some trouble understanding is the fact that if i have one thrust::sort it takes 15 miliseconds, if i have two thrust::sort it takes 17 miliseconds.
For more clarification, i am doing my simulator in opengl (all my buffers are created using opengl), and i use cuda interops in order to sort my buffers with thrust, that uses cuda.
This is the part where i get my buffers and "link" them to cuda
...ANSWER
Answered 2021-Mar-10 at 21:51Two important points could explain you observation:
- The first CUDA function call implicitly initialize the runtime (quite slow).
- The actual content of the arrays to be sorted can/often impact performance of a sort (regarding the algorithm used in the Thrust implementation). Once data are sorted, they can be sorted faster because they are already sorted.
- Thrust make few synchronizations (ie. it calls
cudaDeviceSynchronize
) in many provided functions in order to ensure returned data transferred from the GPU can be safely read from the CPU side. It also internally use such kind of synchronization when multiple interdependent CUDA kernels are submitted regarding the result of the computed data (you can see that with the Nvidia profiler). Regarding the previous asynchronous CUDA calls made before this function, the over-synchronization can add an unwanted overhead.
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