Questions tagged [gpu]

Graphical Processing Unit - a specialized, relatively inexpensive hardware unit built for fast graphical computations and highly data-parallel scientific computations.

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How can I improve this matrix product calculation in OpenCL?

I am trying to compute a matrix-matrix product of N stacked complex double N x N matrices. For simplicity, I assume N = 512. I have written code in C++ parallelized with OMP and using OpenBLAS for the ...
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GPU vs CPU FLOP counts

I apologise if this is somewhat of a rookie question. So, from my understanding, on a GPU board, far more of the space is allocated to ALUs compared to CPUs which have far more cache available. This ...
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Solving DAE in Julia using GPUs

I'm trying to solve a Differential Algebraic Equation (DAE) in Julia which is very computationally expensive using GPUs. I'm brand new to Julia and don't have much experience coding with GPUs. The ...
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How amenable is this 2D Frenkel–Kontorova-like energy minimization problem in Python to the use of a modest PC + GPU? (Heavy reliance on indexing)

@Richard's answer to Going to try to move some of my scipy/numpy calculation to a new GPU, how to avoid disappointing results? is quite helpful, and as promised I've added a simple running example ...
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Going to try to move some of my scipy/numpy calculation to a new GPU, how to avoid disappointing results?

update: I've refactored the question based on helpful advice in the linked meta. I'm a heavy user of Python's NumPy and SciPy (and not much else) and for years I could run anything I need on my laptop....
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PETSc-like library for Julia

I want to build an application for Material Point Method (and probably other meshfree methods too) in Julia and I am looking for library for direct and iterative solvers that can help me with it. One ...
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3 answers
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Optimization on MCMC codes

I am looking for MCMC codes with a GPU suport (like NVIDIA or OpenCL libraries) to make faster run chains. If someone could have a state of the art ...
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Solving multiple linear regression in parallel

I am working on a problem where I need to solve approximately 500 Million Linear Regressions (OLS). What would be the most efficient way to do this (e.g. using GPU or a some framework that can do this ...
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hardware agnostic (GPU/CPU) sparse linear algebra C++ solvers framework/technology

I am looking for recommendations on matured C++ solver for Linear Sparse Algebra problems. The goal is to select between more or less GPU hardware agnostic libraries/frameworks that can be compiled on ...
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1 answer
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MATLAB : find an algorithm to inverse quickly a large matrix of symbolic variables

I have to solve the equality between 2 matrixes 12x12 containing a lot of symbolic variables and with which I perform inversion of matrix. There is only one unknown called "...
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Methodology to develop parallel GPU simulations

I'm quite new to GPU or in general parallel programming. I am working on a Lattice-Boltzmann simulation that should be parallelized on GPU's. I wanted to asked more experienced people how to attack ...
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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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How to properly calculate CPU and GPU FLOPS performance?

Problem I'm trying to calculate CPU / GPU FLOPS performance but I'm not sure if I'm doing it correctly. Let's say we have: A Kaby Lake CPU (clock: 2.8 GHz, cores: 4, threads: 8) A Pascal GPU (clock: ...
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Hardware supporting floats with fraction beyond 64 bit

Is there any computation accelerator (like a GPGPU) available, that natively (this means in hardware, not emulated by a library) supports arithmetics using floating point numbers with a fractional ...
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2 votes
1 answer
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Understading memory sharing in a GPGPU using a lattice example

I am new in the GPUs world, I used them in Matlab ambient so I didn't need to appreciate the subtleties of these devices. I know that a GPU can be divided into multiprocessors (also called Streaming ...
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Implementation of sparse matrix SVD for GPU

I have a sparse matrix $W$ which is almost-squared ($N+1 \times N$) and I would like to know the eigenvalues of $A = W^T W$. $A$ is Hermitian so the eigenvalues are real-positive valued. The usual ...
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Are there any embarrassingly parallel tasks that require a CPU rather than GPU?

I am looking for tasks that are unsuitable for GPUs gain significant speedup as more CPU nodes are added don't require large data transfer or inter-thread communication between nodes. Do any ...
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Solving a complex ODE with large number of variables (>1e6 variables) - best practise?

I have to solve a non-linear ODE of the shape $$\partial_zA=f(A)$$ with $f$ a non-linear function and $A$ a matrix/vector with >1e6 variables (i.e. $A$ is a matrix with >1000x1000 entries). For each ...
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Writing code on the CPU while developing, running it on the GPU when live - which approach?

In my simulations I am using dense matrix-vector multiplications and 2D-fft transformations quite often, for matrix sizes of 8kx8k and up. Hence, I assume that using a GPU is beneficial for speeding ...
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2 answers
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Augmented Dickey Fuller (ADF) test statistics GPU formulation

I have followed different sources of information and achieved the following formulation for the ADF $t$ test statistics. I implemented it to run several hundred thousands of ...
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Consumer hardware for scientific computing?

I'm interested in problems around probability, statistics, and statistical mechanics, and often I find it useful to perform simulations to get some sense of the underlying phenomena. Example ...
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3 answers
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GPGPU computing, software selection

I am using an existing GCC C++ x86 Qt application that filters, displays and stores results computed by some C code. Since the computation by now got too complex for CPUs I intend to port the small C ...
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2 votes
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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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1 vote
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OpenFOAM and CFDEM on GPU

I have a simulation project written for OpenFOAM and CFDEM and would like to find an alternative to run it on GPU since raising the number of cores already provided a promising speed up and ...
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5 votes
2 answers
230 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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Lost on Matrix Inversion

I try to implement some big matrix inversion. My system configuration is Hardware:- Memory: 62.8GiB, Processor: Intel Xeon(R)CPU E5-2670 v3 @2.30GHZ*48 To implement matrix inversion I am using ...
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Use of GPU with respect to CPU

I have research work where I need to compute a matrix inversion. The matrix has a size $31300\times31300$. I am using a universal java matrix package to invert this matrix. But as the dimension of the ...
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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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Accelerate computation speed by using a different syntax [closed]

I was reading a book about Matlab ("Accelerating Matlab with GPU computing - A Primer with Examples" by Jung Suh and Youngming Kim, 2013. Chapter 1.7 Examples). I read an example where it said that: ...
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Compare 64gb dd3 ram with 2gb Quadro M1000M gpu on Lenovo P50

I frequently work with Keras and tensorflow-gpu on my Lenovo P50 workstation which has 64GB ram and a 2GB Nvidia QUadro M1000M GPU. Today while training my model on GPU, it ran into memory error and ...
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Can I convert CUDA core to CPU core and use it as cpu core while running any program?

I was using Metatrader5 and have designed a strategy for trading using MQL5 programming language. While I was running a Strategy Optimization process, I saw the it will need 10,00= iterations or ...
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Why is FLOP(Floating Point Operations Per Second) mentioned as a specification on every GPU?

Counting FLOP may not be representative of the actual algorithm real world performance but still all the GPU manufacturers mention FLOPS as a metric of Performance on GPU. Is there any way that this ...
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6 votes
3 answers
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Performance of kd-tree vs brute-force nearest neighbor search on GPU?

I wonder if there is any study that compares the performance of kd-tree vs brute-force nearest neighbor search on GPU. Post #4 on this page suggests that kd-tree may not be the optimal algorithm for ...
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Porting from MPI to GPU

Assuming that the underlying algorithm can be ported to multi GPU, what aspects should one consider while porting from MPI (on multiple nodes) to multi GPU (again on multiple nodes)? Making use of ...
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Time loop for multiple GPU's

I have a loop that has a similar structure as give below: ...
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2 answers
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Computational Science Hardware Benchmark Database

I am looking for a website/database of computer hardware (CPUs/GPUs) benchmarked with common scientific tools, e.g. *GEMM (see comment below for more info on this tool). Currently, I am quite ...
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1 answer
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Hyperscale Vs Strong-scale HPC

NVIDIA's Tesla GPUs for Servers includes market segments called "Hyperscale HPC" and "Strong-Scale HPC". How different is ...
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2 answers
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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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1 vote
2 answers
2k views

New to CFD, Lattice Boltzmann or Navier-Stokes?

I apologize if some of my questions are naive; I am very new to computer simulations and fluid-dynamics. I am going to start a PhD in early 2017, and I would like to bone-up on some Computational ...
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3 votes
1 answer
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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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How to decide how to parallelize nested loops on GPU

Suppose I have an algorithms which I want to implement ona GPU. The algorithm consists of a main loop, and all iterations of the loop can be run in parallel. Also, each iteration of the loop has an ...
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Fastest way to diagonalize square matrices with c++

I am currently writing software in c++ which solves the eigenvalue problem of sparse hermitian matrices. The size of the matrix depends on the user input, but as an estimation it will roughly be ...
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Matrix free finite elements method [duplicate]

I am Computer Scientist and now I am interested in matrix multiplication on GPUs. My research are focused on matrix free finite elements method where I multiply sparse matrix. Sparse matrix could ...
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9 votes
3 answers
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Is there a constrained nonlinear optimization library like IPOPT that runs on GPUs?

Somebody on my team wants to paralelize IPOPT. (at least some of functions of it). I have not been able to find a GPU implementation of it or a similar package. Nor I've found anything on their docs. ...
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2 answers
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GPU vs CPU calculation

I've been working on calculating large factorials ($N>10^9$) and I was wondering if it wasn't faster to use the GPU to run the calculations on something like openCL. What I realized however was ...
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4 answers
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Easiest Way to Begin GPU Computing

What is the the simplest way to get started using GPU computing? My interests are primarily in neural networks and I would love to start using GPUs, but my time for learning GPU computing is very ...
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5 votes
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Computing entries of a matrix in parallel using GPU

I am trying to solve $Ax=b$ a system of linear equation. The matrix $A=(a_{ij})$ is constructed as $$a_{ij}=\int_0^1\int_0^1 K(x,y)h_i(x)h_j(y) dxdy.$$ The evaluation of integral takes a lot of time, ...
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2 answers
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GPU-enabled Lattice Boltzmann solvers?

Is anybody aware of any GPU-enabled Lattice Boltzmann solvers (preferably on C++/OpenCL and open-source) that would be recommended? I have found Advanced Simulation Library, but it seems to be very ...
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1 vote
2 answers
3k views

How to use the basic Sparse matrix operations (multiplication, .etc) in PyCUDA

I try to use sparse matrix operations in GPU in Python and now try to use PyCUDA with theano. But I can't find how to do sparse matrix and vector multiplication. I only got an example showing how to ...
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1 vote
0 answers
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Is this problem statement good for a GPU?

I am used to using GPU hardware for large scale matrix operations and vectorizing mathematical operations on a continuous space which has been discretized for numerical computation, but this is a ...
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