Questions tagged [cuda]

CUDA™ is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).

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cuSolver Sparse solver fails with CUSOLVER_STATUS_INTERNAL_ERROR [closed]

I'm endeavouring to use cuSolver to solve a sparse linear system. But when I run my code, it fails with CUSOLVER_STATUS_INTERNAL_ERROR. What's going wrong? How does ...
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Unexpected CUDA processing time dependency on thread count [closed]

When calling a kernel function, the number of threads per block should ideally be a multiple of the warp size. This yields more efficient use of resources and lower processing times. However, there ...
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CUDA & Python for numerical integration and solving differential equations

Can anyone please suggest some libraries which allow use CUDA in Python for numerical integration and/or solving of differential equations? My goal is to solve large (~1000 equations) of coupled non-...
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63 views

Source Code for Particle Simulation, Cuda, PyCuda

I am looking for references, pointers to CUDA code that runs particle simulation in parallel, calculating particle trajectories, handling collisions, etc. I've seen some in NVidia source base, but was ...
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what does `cusparse<t>csrsv2_analysis()` do?

In cuSPARSE, you can solve a sparse triangular linear system by calling cusparse<t>csrsv2_solve(). However, you need to call ...
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CUDA and implicit array expansion

I am retrying this question since I didn’t do so properly last time: I have implement a simply c++ CUDA example that takes A [m x 1] and B [1 x N] and adds them element wise with what I am used to ...
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1 answer
175 views

Solving triangular matrix equations on a GPU

Suppose I have these two $N\times N$ lower triangular banded matrices: $A = \begin{bmatrix} a_0 & & \\ a_1 & a_0 & \\ a_2 & a_1 & a_0 \\ a_3 & a_2 & a_1 & a_0 \\ &...
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Matrix requirements for cusparse*csrgemm2

I would like to perform a matrix multiplication like: $C=A*B*A'$ using cusparse library function cusparseDcsrgemm2. To do this I split it into two matrix-matrix multiplications where all matrices ...
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Implementing adaptive timestepping in CUDA

I want to implement a CUDA solver for the 2D shallow water equations using adaptive timestepping with a Courant number fixed by the user. The algorithm pseudocode looks something like this: ...
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2 votes
0 answers
84 views

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

I'm using cuFFT to do some 2D FFTs on matrices of size 2048x2048 or larger. The FFTs are preceded and followed by various scaling operations. These scaling operations are memory-bound, so they take ...
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5 votes
2 answers
206 views

GPGPU language for AMD?

Nvidia seems to be dominating the HPC / GPGPU computing landscape with CUDA. If I want to write a scientific application using and AMD GPU, what is the preferred language these days? I believe it used ...
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Demo example for OpenFOAM with CUDA

I am looking for a simple usage example/demo of OpenFOAM + CUDA and would like to understand how exactly OpenFOAM benefits from CUDA. The thing is I do not have any background in fluid dynamics and so ...
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CPU and GPU influence on task parallel execution performance

This question is mainly about hardware, but also about software. In my current work I have approximately 68 millions of combinations that I am iterating through, in parallel. For each of those ...
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2 votes
2 answers
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Which python library for GPU sparse linear system solver library

I have a fluid dynamic solver written in python which I want to accelerate by moving the most expensive computations to the GPU. Ideally all arrays and sparse matrices used in my code should remain on ...
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Algorithm design to filter on 5,000 stocks each of which has 4 months worth of data points

I want to filter on 5000 stocks, each of which has 4 month or more worth of data (>= 500 data points each). my filtering criteria will be based on 8 calculated values from the data points. for example,...
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1 answer
575 views

Classifying Marching Cube voxels from SPH output data using CUDA

So I have been working on a Smooth Particle Hydrodynamics (SPH) simulation and I am trying to implement the Marching Cubes (MC) algorithm to visualize my SPH output. I understand the MC algorithm well ...
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Irregular data access on CUDA [closed]

I am trying to parallelize a program with CUDA that has irregular memory access. To explain what I am talking about, I have attached two figures. In the first figure, I have plotted the indices of the ...
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8 votes
3 answers
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The real myth of GPU (specifically CUDA) really speed up FEM/CFD

Now I have been believing that FEM/CFD is supposed to be faster on a GPU unit - here I am using CUDA as solid example. However, I have not been able to find a convincing paper where the benchmark ...
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7 votes
1 answer
215 views

What would be a good approach to solving this large data non-linear least squares optimisation

Introduction to Problem I'm using a Truncated Signed Distance Function to perform 3D reconstruction from depth images. Essentially I have a large voxel grid where each voxel contains the signed ...
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3 votes
2 answers
205 views

HPC reading material

I am an undergraduate, and enthusiastic about HPC. I am currently familiar with the tools OpenMP, MPI, CUDA, OpenCL, thrust libraries etc. But I want to know the core functioning of these tools, I ...
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3 votes
1 answer
2k views

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

I was previously running my neural networks using the Lasagne library to build and train neural networks in Theano on an NVIDIA GTX 750 Ti. I'm using a genetic algorithm to tune the hyperparameters of ...
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1 vote
1 answer
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Efficiently rotate vector in 2D (and 3D)

I need to efficiently rotate a 2D (and 3D) vector in a CUDA kernel. I was thinking about generating random unitary rotation matrices. I don't need to know the angle, it just has to be randomly ...
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4 votes
1 answer
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Efficient Successive Over Relaxation using Cuda?

I recently implemented Successive Over Relaxation using Cuda as a part of my course project and was curious to know how I can make the code more efficient. I'm using Red/Black SOR scheme which is ...
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2 votes
2 answers
329 views

using GPUs before CUDA and OpenCL

Before there was CUDA or OpenCL people were using GPUs for computation. I am trying to find out how they did that -- because I want to press my Rasberry Pi's GPU for computing and it does not seem to ...
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0 votes
1 answer
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How can I use Scipy to fit data generated from a C++ model?

I currently have a functioning and blazing fast model written in C++ and CUDA. However, I'd like to use Scipy.minimize to fit the model to some experimental data. I was hoping it would be easy, but ...
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2 votes
1 answer
362 views

CUDA Fortran: Multi GPU Programming and memory allocation

I am writing a program that is supposed to use multiple GPUs on a single node using CUDA Fortran. Although I've looked through the Portland Group CUDA Fortran Reference, I am still unclear about how ...
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5 votes
2 answers
612 views

Machine precision and local error

I'm working with an RKF45 integrator that I have programmed using CUDA C++ on my GPU and am pondering a few questions as I'm trying to track down some issues with my code. I'm using double ...
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6 votes
1 answer
2k views

How to get proper parameters of SPH simulation?

I'm implementing basic fluid flow simulator using SPH method basing on e.g. https://www10.informatik.uni-erlangen.de/Publications/Theses/2010/Staubach_BA10.pdf. EDIT (dead url): https://www10.cs.fau....
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8 votes
5 answers
2k views

Good Finite Element Library for a small project

I'm currently working on this project and I have a basic structural analyzer that uses the finite element method. Essentially, I turn each block into a set of trusses, construct a stiffness matrix ...
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35 votes
1 answer
14k views

CUDA vs OpenCL as of late 2013

How do CUDA and OpenCL compare to each other as of late 2013 from a programmer's perspective? My group is thinking about trying to make use of GPU computing. Would we be limiting ourself ...
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2 votes
1 answer
135 views

Multiple independent random number streams

Having multiple streams of pseudo-random numbers known to be independent and with a uniform distribution I want to do Monte Carlo simulations in parallel. In other words, one thread will have a full-...
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8 votes
1 answer
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Why am I getting so much error for my Runge Kutta Fehlberg solver?

My current project is a reprogramming of a protein folding model involving the solution of thousands of ODEs in C++. I've been making some stop and start progress as I'm writing the solver to run ...
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2 votes
1 answer
191 views

Numerically efficient way to compute sparse-matrix arithmetic on GPU?

Can anyone tell me some very good/efficient numerial algorthims for GPU/CUDA to compute multiplication/ between sparse matrices (its good if you can recommend me some research papers)? I googled ...
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1 vote
2 answers
167 views

Looking for super computer technology suggestions

I'm writing some image processing software to detect bubbles in oil at work. One of the image filters I need (Perona Malik) seems like it will take a long time to compute. (It involves solving some ...
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2 votes
0 answers
467 views

Prediction model on GPU [closed]

I am doing a small project at school. I have done my code implementations in CUDA and did some performance measurements with real values, i.e. running the program with different number of threads, ...
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10 votes
1 answer
818 views

cuda and numerical methods with implicit time discretization

I am looking to port some code that resolves a set of partial differential equations (PDE) by the finite volume method in IMPLICIT form (for the time discretization). As result there is a tridiagonal ...
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18 votes
3 answers
6k views

Solving unconstrained nonlinear optimization problems on GPU

I am trying to solve some unconstrained nonlinear optimization problems on GPU (CUDA). The objective function is a smooth nonlinear function, and its gradient is relatively cheap to compute ...
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1 vote
0 answers
497 views

CUDA Mandelbrot Set effective bandwidth and optimization

I was reading through this article (very good article and excellent blog BTW) to do some measurements in my (very simple) implementation of the Mandelbrot Set. I'm using a Quadro 2000D card which has ...
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2 votes
0 answers
592 views

Cusp Library performance worse than PETSC (GMRES 200 iterations) Why?

I wanted to compare the speeds of the GMRES implementations in the CUSP and the PETSc libraries. The matrix (A) used for testing was a 3d Laplacian matrix obtained by using the 7 point stencil on a ...
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11 votes
3 answers
2k views

Thrust for GPU programming

I'm very new to GPGPU programming so please forgive me if the question is not particularly appropriate. From what I understand GPU programming is a very intricate piece of engineering work when ...
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