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21 votes
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The real myth of GPU (specifically CUDA) really speed up FEM/CFD

Here's the deal with GPUs. On a GPU, every single core is slow. Really slow. However, you have thousands of cores. If you can effectively use the thousands of cores at a time, then your algorithm will ...
Chris Rackauckas's user avatar
17 votes
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CUDA & Python for numerical integration and solving differential equations

Julia's DifferentialEquations.jl is all GPU-compatible. If you make your arrays GPU-based arrays, then the solver recompiles to be all on the GPU (no data transfers). For example: ...
Chris Rackauckas's user avatar
5 votes

The real myth of GPU (specifically CUDA) really speed up FEM/CFD

To extend Chris Rackauckas's exhaustive answer with a reference try to look pdf by Torres, Gonzalez-Escribano, Llanos. It is about the tuning of a gpu, that is an important aspect for performance. ...
Mauro Vanzetto's user avatar
5 votes

Why am I not seeing faster neural network training after upgrading to a vastly better GPU?

I suppose, you right and your network is not that big to 100%-utilize the GPU. The bottle-neck here seems to be not the GPU itself, but the transfer rate between RAM and VRAM and here the difference ...
Vlad's user avatar
  • 114
5 votes
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What would be a good approach to solving this large data non-linear least squares optimisation

I don't know much about tracking implicit surfaces, so I'm just going to start with the optimization problem and go from there. The optimization problem is, at the core, nonlinear least squares, and ...
Nick Alger's user avatar
  • 3,143
2 votes

HPC reading material

The Intel OpenMP Run Time library has been open sourced, so you might have look at a few functions in there. There are many open source MPI libraries (MPICH2, OpenMPI, MVAPICH2, etc.), and the MPI ...
Bill Barth's user avatar
  • 10.9k
2 votes

Which python library for GPU sparse linear system solver library

I have found pycuda particularly useful as wrapper for cuda in python. Especially the section on metaprogramming is useful if you are interested in building more sophisticated frameworks. It's a ...
nluigi's user avatar
  • 277
2 votes

GPGPU language for AMD?

I can't speak to how you would best work with an AMD GPU. However, of the languages you list CUDA could be considered the lowest level, highest-performance language for general applications. This is ...
Richard's user avatar
  • 3,961
2 votes

Demo example for OpenFOAM with CUDA

I suggest to start form this page, where you can find different project related to OpenFoam that use GPU. Keep in mind that OpenFoam was born with the intent to resolve practical case in applied ...
Mauro Vanzetto's user avatar
2 votes
Accepted

Matrix requirements for cusparse*csrgemm2

It seems that cusparse library expects the CSR matrix to be ordered. If the matrix is not ordered, the cusparse functions fail. Ordering helps to fix the above mentioned issue.
vydesaster's user avatar
2 votes

what does `cusparse<t>csrsv2_analysis()` do?

Structural and numerical zeros describe how zero values in your matrix are stored. Structural zeros are zeros that are implied to be zero because they are not present in the data structure. ...
Neil Lindquist's user avatar
2 votes
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How can I convert a C program into a CUDA program?

Your steps in the example are correct but it is hard to say without much information. If you are doing something akin to a linear equation approximator or eigenpair approximator, where most of the ...
Mephistopheles Faust's user avatar
1 vote

CUDA & Python for numerical integration and solving differential equations

I have seen that people use CuPy; and scikit-cuda. But, I don't see that any of those provide differential equations capabilities. Looking around, I found CudaPyInt and it uses PyCuda.
nicoguaro's user avatar
  • 8,490
1 vote

Source Code for Particle Simulation, Cuda, PyCuda

After asking the q, I was able to find a sample code; The PyCuda code of this paper, COMPARISON OF PYTHON 3 SINGLE-GPU PARALLELIZATION TECHNOLOGIES, is below. It is written for 2D. http://ceur-ws.org/...
BBSysDyn's user avatar
  • 239
1 vote
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Solving triangular matrix equations on a GPU

1) Is there a mathematical trick to simplify the above matrix equations? As in, only having to do one inverse operation instead of two. Yes: Schur complement formulation. Your system is equivalent to ...
Federico Poloni's user avatar
1 vote

Fusing callbacks with FFTs: an open-source GPU FFT implementation?

This is a pretty old question, but rocFFT is an open-source GPU FFT library for AMD GPUs. It's written in HIP, so it could likely also work on NVIDIA GPUs with a bit of work.
Malcolm's user avatar
  • 169
1 vote

GPGPU language for AMD?

I don't have enough reputation, so I (have to) post an answer instead of a comment. An alternative is to use the HIP compiler with its own language. See here: https://github.com/ROCm-Developer-...
dweber's user avatar
  • 131
1 vote

CPU and GPU influence on task parallel execution performance

Both CPUs you list are much more powerful than your existing laptop and assuming you're getting even reasonable parallelism out of the loop should contribute significant speedup. Without knowing your ...
Richmond Newman's user avatar
1 vote

Which python library for GPU sparse linear system solver library

Pycuda is one of the more pythonic way to handle cuda in python as @nluigi suggested. If you are open to call C/C++ code inside python there is also CUSP: Cusp is a library for sparse linear ...
Mauro Vanzetto's user avatar
1 vote

Classifying Marching Cube voxels from SPH output data using CUDA

It is a different approach but maybe you could do a point cloud surface reconstruction using total variation denoising as in here. They have a demo code that you could use as a base for your ...
jcperezma's user avatar
1 vote
Accepted

Efficiently rotate vector in 2D (and 3D)

Some of the standard methods for random rotations in 3D (Sphere Point Picking) are listed on Mathworld. On a CPU, Marsaglia's method is quite efficient, because it avoids expensive $\sin$ and $\cos$ ...
Jannis Teunissen's user avatar
1 vote

How to get proper parameters of SPH simulation?

A few constraints that usually work in scientific SPH (weakly compressible) computations: particle radius or influence radius, $\Delta$: define it arbitrarily to set the resolution. smoothing radius, ...
BalazsToth's user avatar
1 vote

cuda and numerical methods with implicit time discretization

This problem lends itself to a highly vectorized form. As you noted, the ADI method gives a few steps of tridiagonal systems. Since it's in the form of linear equations, you can use CUsolver and ...
Chris Rackauckas's user avatar

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