Out of memory when performing operation on sparse matrix comsol. I got some code for you.

Out of memory when performing operation on sparse matrix comsol There are many ways to address this. " Read the explanations in the install & operation documentation (comsol_iog. Moved Permanently. The proposed implementation is based on Hi In the definition node you define an "operator" that applies to something you define elsewhere. FORUM "Out of memory" BLOG The Elephants of Materials Science: SMAs Never Forget Their Shape; BLOG Intro to the What, Why, and How of Shared Memory Computing; FORUM Out of Memory !! KNOWLEDGE BASE Out of Memory During Assembly If your sparsity is 1, this means a sparse representation needs 50% more memory. EST. I got some code for you. The speedup depends on the processor load. % COMSOL Multiphysics Model M-file % Generated by COMSOL 3. Using Pysparse, you can build the matrix incrementally using the link list format, then convert the matrix into sparse Out of memory during assembly BUT the mesh number is just 3608. 11 minutes for two 10,000 * 10,000 matrices. I'm trying to run the example in Batteries and Fuel Cell Module (sofc_unit_cell), but encountered the following problem: Failed to find a solution for the initial parameter. With the new hardware it worked for me. 0. 5 hours for 20,000 * 20,000 and 30 hours for (500k*18k) times (18k*18k). The required memory and the computational time for one iteration with BiCGStab is constant; that is, the time and memory requirements do not increase with the number of iterations as they do for GMRES. and it never goes beyond 1. ini file located in the subdirectory bin/$arch in the COMSOL installation directory, where $arch corresponds to the platform you are using. In the definition you only specify entities where it applies and integration information (this is different from v3. In the limit of mesh refinement, any combination of element orders in different physics will give the same results, but the convergence may well be very slow and oscillatory. sparse doesn't contain a sparse, symmetric matrix format. Reported virtual memory (blue) and physical memory (orange) needed versus problem size, in terms of millions of DOFs, for a model involving heat transfer in solids. I had both problems and solved it by extending the working memory from 16GB to 32GB and a new hard-drive. high-performance computing, sparse matrix-vector multiplication, SpMV library, multicore, processing-in-memory, near-data process- Memory Supporting 1TFLOPS MAC Operation and Various Activation Functions for Deep-Learning Applications, ISSCC, 2022. “Sparse matrices provide a more efficient way to store and process large datasets with a high degree of sparsity, offering significant benefits in terms of memory ofc, simplest solution is using Java or C++ (or anything else), however I am dealing with very large matrices (basically large enough that fitting them into memory is out of question) and it makes matrix manipulation in reasonable speed quite complicated as it requires keeping only chunks in memory and IO overhead for very large number of reads and writes required to 1 Check the Version Number. Computational complexity also depends linearly on the row size m and column size n of the matrix, but is independent of the product m*n, the total number of zero and nonzero elements. ; A value is inserted into the matrix at a given row and column using the insert technique. feature_sample is a randomly generated boolean array of the shape (138106,) Ex of it : [True True False False . Out of memory operation sparse matrix Messages: Out of memory operation sparse matrix Stack trace: at lsspooles. 2011, 04:56 UTC−5 0 Replies . pdf for V4, install. Modify the number in the Out-of-memory messages can occur when the COMSOL Multiphysics software tries to allocate an array that does not fit sequentially in memory. Posted 2011年3月13日 GMT-4 15:02 Modeling Tools & Definitions, Parameters, Variables, & Functions 5 Replies Puneet Malhotra getting Error: 6192 Out of memory when performing operation on sparse matrix. EDT 3 Replies . 967 3 3 gold badges 17 17 silver badges 26 26 bronze badges. Why do I encounter out of memory errors in MATLAB when performing sparse matrix multiplication routines? Follow 4 views (last 30 days) Show older comments. I am still relatively new to COMSOL so any help would be appreciated! Thanks! The matrix-free representation allows evaluation of matrix-vector products without assembling the matrix. int8) Directly constructing the csr_matrix will also allow you to go further with the maximum matrix size:. However, I always encounter this problem when perform 'compute': COMSOL error: Size of sparse matrices disagree. Posted 13 déc. Not all parameter steps returned. Hi when moving to PZT and 3D you need the full tensor represenation of several variables, this increases substantially the sparsity and sizes of the matrices, so the out of memory is much quicker there if you operate from a "small" laptop or a 2Gb RAm PC. COMSOL error: Size of sparse matrices disagree. But the memory allocation for comsol, (at bottom of the window) remains around 2GB or † A new automatic option for computing the in-core memory for the MUMPS and PARDISO direct solvers is now the default instead of specifying the in-core memory directly. We addressed the high communication volume requirements of this kernel by proposing graph and hypergraph partitioning models which can minimize multiple volume-based communication cost metrics simultaneously in a single Chapter 1 Introduction Sparse-matrixdense-matrixmultiplication(SpMM)iswidelyconsideredtobeanim-portantproblemacrossmanyfieldsincludingbiology,finance,andmachinelearning Time Complexity: O(N*M), where N is the number of rows in the sparse matrix, and M is the number of columns in the sparse matrix. I put the double * just in this question, not in the real code. Discussion Closed This discussion was created more than 6 months ago and DoF. 40Ghz and 12. Canceled Time: 9 s. See also: Knowledge Base 1186: Out of memory during assembly. Please login with a confirmed email address before reporting spam Out of memory during LU factorization. Out of memory, solution does not converge, failed to find solution. 6. Is it ? Can this be a mesh problem, even though I have the "Out of memory" problem ? Thanks In the original version, M is a three-dimensional matrix, I don't know whether the memory issues maybe occur because of my modification transforming M to a 2D scipy. The master element matrices of each pattern are pre-computed while the storage of the individual element matrices is avoided leading to a significant reduction in memory requirements, especially I have two sparse matrices A (logical, 80274 x 80274) and B (non-negative integer, out-of-memory; octave; sparse-matrix; matrix-multiplication; or ask your own question. *, a dense matrix is built, and OutOfMemoryError() is raised! For instance, n = 10_000_000 v = rand(n) A = sprand(n,n,2/n) v . 逸鑫 高 Note that while COMSOL employees may participate in the discussion forum, [COMSOL_Users] Out of memory operation sparse matrix? zhang_hfeng11 2010-03-17 20:17:05 UTC. mph; 10 Replies Last Post Nov 21, 2016, 2:21 p. Why do I encounter out of memory errors in MATLAB when performing sparse matrix multiplication routines? I have a computer with plenty of memory. Pysparse, however, does. Knowledge Base 1030: Error: "Out of memory" Solution. Attachments: 3D_1. Variable names which are defined for use in modeling and postprocessing always represent scalar values. Figure 1. 25 GB vitual memory, plus whatever it offloads during operation in Client/Server mode should be able to do much more complex simulations than this, but it's not. solver. We propose an efficient distributed out-of-memory implementation of the non-negative matrix factorization (NMF) algorithm for heterogeneous high-performance-computing systems. To do so, expand out the Study settings and go to the Time-Dependent Solver branch, Fully Coupled subfeature, Method and Termination section. The solver reads some of the blocks into memory and performs the LU-factorization on the part that is currently in memory. Is there a particular version of Java we should have installed on a Windows 7 machine? have been introduced that structure memory accesses to improve the performance of sparse matrix operations. AFAIK scipy. This can reduce the memory usage significantly for solver algorithms that only use the matrix to multiply a vector, specifically: • Hello K_Patel Your Discussion has gone 30 days without a reply. In segregated group 2: Returned solution is not converged. 36 GB Virtual memory: 21. 2. . 25 GB physical memory, 4. Tensors are higher-order generalization of matrices, and they pro- TKRP) operation, which makes up approximately 90% of the total execution time Efficient, Out-of-Memory Sparse MTTKRP on Massively Parallel Architectures ICS ’22, June 28–30, 2022, Virtual Event, USA Also, there IS a version specific issue here. This is very difficult to do on my dataset, and furthermore would destroy the sparsity of the matrix. The following method should reduce the amount of device memory required for the calculation of A x AT. 0. In scipy, we can construct a sparse matrix using scipy. Posted 2011/03/13 15:02 GMT-4 Modeling Tools & Definitions, Parameters, Variables, & Functions 5 Replies Puneet Malhotra Matrices and Matrix Operations. jni. Out of memory operation sparse matrix Stack trace: at lsspooles. The original code OP posted generates an out-of-memory on my Win32 XP machine through R2010b, but is fine for R2011a onwards. It takes about 0. Posted 2010年3月17日 GMT-4 16:10 0 Replies . If you do not hold an on-subscription license, you may find an answer in another Discussion or in the Knowledge Base. sparse import csr_matrix def foo(*args): dim_x = 256*256*1024 dim_y = 128*128*512 . cpp, row 1837, (Undefined value found in the stiffness matrix. Both i and j are 222263280-by-1 int32 vectors while v is a 22226 However, using virtual memory is slower than storing data in RAM, therefore the virtual memory will not, by default, be much greater than the installed RAM memory. sparse(3, [0, 2], [1. femEig(Native Method) at Out of memory operation sparse matrix Stack trace: at lsspooles. The matrix is available as a list of variables with names <name><i><j>, where <name> is the namespace set in the Name field, and <i> and I am having GC overhead limit issues too. I am construcing a stiffness matrix in finite element computation. 7s to multiply two 1000*1000 matrices. 24 GB | 1. In this paper we revisit the performance issues of the widely used sparse matrix-vector multiplication (SpMxV) kernel on modern microarchitectures. To loop a variety of sparse matrices from the scipy. cpp, row 197, at com. M. Dear all, I'm a new user in COMSOL 5. So that your data set will run on different clusters (RDD). Any trademarks referenced in this document are the property of their respective owners. linalg import Vectors sparse = Vectors. femStatic(Native Method) In out- of-core the solvers stores part of the stiffness matrix in the hard drives/SSDs and thus the performance drops abruptly (HDs are tremendously slow in comparison to RAM memory). I am wondering if there is an existing data structure for sparse 3d matrix / array (tensor) in Python? p. ; Open the About COMSOL Multiphysics dialog box. Auxiliary Space: O(K), where K is the number of non-zero elements in the array. X[:, feature_sample] Here X is of the dimension : [8000000, 138106]. The default setting is Automatic, which switches the storage to disk (out-of-core) if the estimated memory (for the LU factors) is exhausting the physically available memory. COMSOL requests memory from the operating system and will always use both the physical RAM and virtual memory available on your system. This array can be split into blocks (maybe disjointed, maybe overlapping) and each process then handles its private block. , time-dependent) study in COMSOL Multiphysics ®, it is important to have your model set up so that the initial conditions are consistent with the loads and boundary conditions. From the Matrix size list, choose a matrix size from 1-by-1 to 9-by-9; then enter the matrix elements in the table below. From the Out-of-core list, choose On to store all matrix factorizations (LU factors) as blocks on disk rather than in the computer’s memory. * A # ERROR: OutOfMemoryErr As the subject says, when I try to scale the values of a large sparse matrix using . 3. I have the same problem, that comsol just uses the RAM between 30-50GB instead of 110GB. I have two variables in my MATLAB workspace: xx Looks like you are simply running out of memory. Your problem should solve on your computer if you use I run a static stress analysis using Comsol combined with MATLAB, I put the analysis program in a "for" loop using Matlab, the program will stop at certain loop with error when moving to PZT and 3D you need the full tensor represenation of several variables, this increases substantially the sparsity and sizes of the matrices, so the out of memory is much 1. *, a dense matrix is built, and OutOfMemoryError() is A Hermitian matrix (or self-adjoint matrix) is a complex square matrix that is equal to its own conjugate transpose. float64'>' with 1 stored elements in Compressed Sparse Row format> However, I've read that prior to performing PCA, one should center the matrix (subtract the column mean from each column). The information provided may be out of date. Given a Scipy CSC Sparse matrix "sm" with dimensions (170k x 170k) with 440 million non-null points and a sparse CSC vector "v" (170k x 1) with a few non-null points, is there anything that can be done to improve the performance of the operation: resul = sm. Discussion Closed This discussion was created more than 6 months ago and has been closed. Please login with a KNOWLEDGE BASE Out of Memory; FORUM Extracting frequency dependent matrices (of a nonlinear eigenvalue problem) I am construcing a stiffness matrix in finite element computation. ----- Compile Equations: Frequency Domain in Study 1/Solution 1 (sol1) So it looks like it is using more than 6 GB and still is going out of memory. where <soltag> is the solver node tag used to assemble the system matrices and out is a cell array containing the list of the matrices to Now compare both solution vector U and U1 computed by COMSOL Multiphysics and by the matrix operation, The following pertains to the Direct attribute node. when moving to PZT and 3D you need the full tensor represenation of several variables, this increases substantially the sparsity and sizes of the matrices, so the out of memory is much quicker there if you operate from a "small" laptop or a 2Gb RAm PC. Or you have to simplify your model. below is the sample code, from pyspark. Since you have 200k columns your correlation matrix would have a size of 320GB. When solving either a linear or a nonlinear problem, a set of linear equations are solved. Both i and j are 222263280-by-1 int32 vectors while v is a 22226 The London School of Hygiene & Tropical Medicine (LSHTM) is delighted to be offering a number of exciting studentships in a range of subjects and topics for our PhD programmes starting September 2018. Returned solution is not converged. EDT 0 Replies . All linear system solvers above work on general sparse linear systems of the form Ax = b and use LU factorization on the matrix A to compute the solution x. On the gpu, memory accesses to host pinned ddr memory is allowed and Uni ed Memory (uvm) accesses work similar to the \cache" This reduces the number of operations As the subject says, when I try to scale the values of a large sparse matrix using . We'll use the following ideas: since the input array (A) only takes on values of 0,1, we'll reduce the storage for that array down to the minimum convenient size, int8, i. This can Note: This discussion is about an older version of the COMSOL Multiphysics ® software. (c Del u)=0. es. Amir Hossein Zakeri. But when trying to solve the first part of the equation: r = dot(C, Y) The computer crashes due Memory limits. In doing so, they use a preordering algorithm that permutes the columns of A to minimize the number of nonzeros in the L and U factors. Why? when moving to PZT and 3D you need the full tensor represenation of several variables, this increases substantially the sparsity and sizes of the matrices, so the out of memory is much quicker there if you operate from a "small" laptop or a 2Gb RAm PC. If "out of memory" occurred, is it helpful if I select the Out-of-core check box, and increase the number of In-core memory (MB) to fix this error? 2. ; The sparse matrix is printed using the print technique. MathWorks Support Team on 27 Jun 2009. T@M Out[267]: <100000x100000 sparse matrix of type '<class 'numpy. For instance, if your system has m processors and n of them are used by other active programs, do not set the number of cores to a number that is greater than m − n . In both cases, I use MUMPS with exactly the same options, Out of memory. Also, I havent tried yout b The cor function calculates correlation for each pair of columns (or rows depending on the dim parameter). 0 Go of RAM. If using the Windows ® operating system, the dialog box can be found in the File menu under Help. so it is swapping out to disk. The blocks of data are then written back to disc and new blocks are read into memory. pdf in V3. Note: This discussion is about an older version of the COMSOL Multiphysics ® software. Clearly, adding more memory to our computer would let us solve a larger model, and we can linearly extrapolate to predict the memory requirements. 5a (COMSOL 3. sparse import * def iter_spmatrix(matrix): """ Iterator for iterating the elements in a ``scipy. lil_matrix (instead of coo) s. astype(np. I encourage you to take a look at Y is initialized randomly and C is a very sparse matrix with only a few numbers out of the 300k on the diagonal will be different than 0. Instead, all such expressions are written in terms of component variables, often with names derived For your case I would recommend using the data type np. lil_matrix() etc. 5. I believe my computer should be powerful enough to do it : 2 * 2. Both i and j are 222263280-by-1 int32 vectors while v is a 22226 The importance of Sparse Matrix dense Vector multiplication (SpMV) operation in graph analytics and numerous scientific applications has led to development of custom accelerators that are intended In addition, you can choose a matrix-free format, which you choose as Free. Choose Off to not store the matrix factorizations on disk. Many graph but where cache mode does not perform well. Popular preordering algorithms COMSOL error: Size of sparse matrices disagree. This work aimed to improve the performance of sparse matrix dense matrix multiplication on distributed memory systems. BiCGStab uses approximately the same amount of memory as GMRES uses for two iterations. *_matrix`` This will always return: >>> The computer then runs "Out of memory" (also by starting from a Finer mesh and then increasing the maxi/mini elements size and the resolution of narrow regions). P. Messages similar to this are returned for nonlinear problems that fail to converge, but also sometimes for linear problems. one byte per elementsince the B array is just the transpose of the A array, there is no need to 大多数操作系统也会使用硬盘（虚拟内存）来存储数据。然而，使用虚拟内存比在 ram 中存储数据更慢，因此默认情况下，虚拟内存不会明显大于安装的 ram 内存。comsol 向操作系统请求内存，并总是使用系统上可用的物理内存和虚拟内存。 2) 检查 comsol 模型的大小 Out of memory. Is it ? Can this be a mesh problem, even though I have the "Out of memory" problem ? Thanks The information provided may be out of date. 70 GB. I am solving an equation of type del. 2) Check the size of your COMSOL model So you're right - the result of sparse on this matrix should be some kind of empty matrix since all elements are zero and so have been squeezed out. Usman Khan . When a full matrix has a small number of nonzero elements, converting the matrix to sparse storage typically improves memory usage and Discussion Closed This discussion was created more than 6 months ago and has been closed. s. Using Spicy, it is very difficult to create large sparse matrix and your system memory might not support. See https://www. Sparse matrix-matrix multiplication also has applicability in data analysis problems as it is a foundational kernel for the GraphBLAS e ort [8]. The two numbers in Figure 3-13 displayed as 1. float64) n = A. A good practice is to store matrices with few nonzero elements using sparse storage. Which leads me to believe that there is something in the indexing or concatenating that changed between these versions with regards to sparse matrices and how they use temporary memory I am construcing a stiffness matrix in finite element computation. Memory consumption is usually a key problem. Hi, I am a new user of COMSOL Ver. I use TAUCS solver since the matrices are symmetric, and no matter what it always returns me "out of memory during sparse matrix operations" when i go beyond 50k elements. Here since column slicing is being done csc matrix is more efficient for Extract the matrices of the COMSOL Multiphysics linearized system with the function mphmatrix. Posted 9 set 2024, 02:44 GMT-7 Version 6. matrix = dok_matrix((dim_x, dim_y), dtype=np. I am trying to solve a simple 3D problem having diffusion and chemical reaction within the subdomain. 5a (in acoustic and heat transfer transient). Send Private Message Flag post as spam. vstack((A, B), format='csr') A = A. Both i and j are 222263280-by-1 int32 vectors while v is a 22226 Discussion Closed This discussion was created more than 6 months ago and has been closed. Start COMSOL Multiphysics ®. Posted 2011年3月13日 GMT-4 15:02 Modeling Tools & Definitions, Parameters, Variables, & Functions 5 Replies Puneet Malhotra In the lower-right corner of the COMSOL Desktop is information about how much memory the COMSOL Multiphysics software is currently using. Out of memory in Matlab - how to do in-place operation on matrix elements? 2. The matrix is quite big, so I can not invert it by hand. If you do not hold an on-subscription license, Out of memory during LU factorization. Peak SpMV perfor-mance is achieved by coupling sparsity pattern analysis with specialized, and in some cases exotic, storage schemes Explanation of the above Program: A HashMap is included in the SparseMatrix class to effectively represent non-zero items. Posted 17 mars 2010, 16:10 UTC−4 0 Replies . e. As it turns out, in many cases, the worst thing that will happen is that your model will simply require more memory and converge to a solution more slowly. This is useful if you need to compute the solution before extracting the matrices or if you have a solution sequence using different Out of memory during assembly. True]. dot(v) ? Currently it's taking roughly 1 second. Check the COMSOL documentation if you are not familiar with that operator. femlab. This can reduce the memory usage significantly This setting chooses a sparse, filled, or matrix-free representation Select the Check for undefined numerical values after each operation checkbox to make COMSOL Multiphysics check The matrix-free representation allows evaluation of matrix-vector products without assembling the matrix. 79 GB Ended at Sep 30, 2024, 4:10:18 PM. But the typical operation for finite element numerical simulations is of sparse matrix-vector type, which is bandwidth-bound, and the bandwidth is typically proportional to the number of memory channels in a multicore From the Out-of-core list, choose On to store matrix factorizations (LU factors) as blocks on disk rather than in the computer’s internal memory. However, using virtual memory is slower than storing data in RAM, therefore the virtual memory will not, by default, be much greater than the installed RAM memory. from scipy. I have created a Physics model via the PDE module which require input from the results of matrix calculations. Now I am using "Rectangular waveguides straight to ring coupler" sample file to study how to use COMSOL. Please login with a confirmed email address before reporting spam Hello, I am modeling 3D Brain in comsol 3. Fatemeh Sharifi . 603, FORUM Out of memory operation sparse matrix; Product Information; Products; Specification Chart; License Options; Your Discussion has gone 30 days without a reply. Segregated group 2 Out of memory during LU factorization. You can specify the solution feature node after which to assemble the system matrices with the property extractafter. But before sparse is even called, zeros(80000) is invoked which will try to create a 80000x80000 matrix of zeros. cpp, row 262, at com. com Lastly, keep in mind that you will always need to perform both a relative tolerance refinement study, as described here: Knowledge Base 1254: Controlling the Time-Dependent Solver Timesteps, and a mesh refinement study, as described The remainder of the operation is carried out according to the single memory-bound Sparse Matrix Vector Multiplication (SpMV) kernel. Divergence of the linear iterations. Please login with a If you still need help with COMSOL and have an on-subscription license, please visit our Support Center for help. S. The right solution is to quote your code: PSA: how to quote code with backticks I’ve edited your post to fix this. 2) Check the size of your COMSOL model Note: This discussion is about an older version of the COMSOL Multiphysics ® software. PDT Version 6. 0, 3. shape[1] # Compute the covariance matrix rowsum = A. Now, assuming that you have enough computational power to handle such task, your best bet is to perform computations pairwise and store the results to a file. This option assembles the matrix vector product when needed. 1, My operation system is windows 32bit, and the internal memory is 2GB . KNOWLEDGE BASE Out of Memory; FORUM Problem in Sparse linear solvers ; BLOG Using Data Filtering to Improve Model Performance; KNOWLEDGE BASE Error: "Out of memory" BLOG Discretizing the Weak Form Equations Because i had several times the error: Out of memory, solution does not converge i tried to change the solver to iterative and GMRES with Out of Core checked, but after 4 hours of solving the message that returns is: Failed to find a solution. Harry Zhang . getting Error: 6192 Out of memory when performing operation on sparse matrix. ini file. Modify the Jacobian update: COMSOL does not assume any legal liability for the accuracy of the data disclosed. Best, Jeff Yi Yan. Type HELP MEMORY for your options. The matrix-free representation allows evaluation of matrix-vector products without assembling the matrix. com/support/knowledgebase/830 and https://www. Follow the guidance given in Knowledge Base 1030: Error: "Out of memory" If your model includes integration coupling operators, this may also cause COMSOL to run out of memory during the assembly step. Add a comment | 1 When solving a transient (i. I suggest to use Spark libraries. The function mphmatrix does not solve the problem as the assembly is performed before the solver node in the solution sequence. Details: Exception: com. Out of memory operation sparse matrix. The variable evaluator used inside COMSOL Multiphysics does not recognize vectors, matrices, tensors or operations on such objects. Please login with a If you still need help with COMSOL and have an on-subscription If you run out of memory during the assembly step, you do not have enough RAM memory in your computer to solve your model. Is it ? Can this be a mesh problem, even though I have the "Out of memory" problem ? Thanks Sparse Matrix Operations Efficiency of Operations Computational Complexity. FlNativeException: Out of memory operation sparse matrix Messages: Out of memory operation sparse matrix Stack trace: at lsspooles. It is common that the amount of available Although one can never be sure from just an error message, I suggest that your problem may be that you created a model that requires more memory than you have. FlSolver. It represents a matrix as an array of column vectors (which means each entry in the array is a column, not a row). If the disk memory is meant, it is really written "Out of disk memory". This would explain why you run out of memory without ever getting close to "saturating" the 110GB. Posted Mar 17, 2010, 4:56 p. Physical memory: 6. m. 75MB (total) when the solver worksI thought it was because If you run out of memory, try to lower the number of used cores as explained in the COMSOL Multiphysics Installation Guide. My machine has huge amounts of RAM. Posted 13 dic 2011, 04:56 GMT-5 0 Replies . 逸鑫 高 Note that while COMSOL employees may participate in the discussion forum, COMSOL Out of memory operation sparse matrix. Please login with a KNOWLEDGE BASE Out of Memory; FORUM Extracting frequency dependent matrices (of a nonlinear eigenvalue problem) When dealing with large matrix: For full matrix, you'd better preallocate memory to avoid memory copy during extending. 73 GB represent the physical memory and the virtual memory, respectively. 1 1 Reply . Out of memory when performing operation on sparse matrix. COMSOL supports as much RAM as you manage to push into your HW, and to my experience "Out of memory" means not the disk memory, but the working memory. Follow the guidance given in Knowledge Base 1030: Error: "Out Open the comsol. 2 (build The computer then runs "Out of memory" (also by starting from a Finer mesh and then increasing the maxi/mini elements size and the resolution of narrow regions). sparse code section I would use this small wrapper function (note that for Python-2 you are encouraged to use xrange and izip for better performance on large matrices):. Posted Sep 9, 2024, 2:44 a. There are 28 void equations (empty rows in matrix) for the variable mod1. Share. t. Posted 4 mag 2013, 12:34 GMT-4 0 Replies . This is important for any time-dependent model, but it is especially notable when performing transient fluid flow studies. ; Matrix addition is done getting Error: 6192 Out of memory when performing operation on sparse matrix. There are 35741 equations giving mode1. sparse. femStatic(Native Method) If you still need help with COMSOL and have an on-subscription license, please visit our Support Center for help. Since Numpy's diagonal functions creates dense matrices, I created C as a sparse csr matrix. Filling a preallocated sparse matrix involves loads of operations, so the best way of creating sparse matrices is by giving the values in one go. Rohan Pillai Rohan Pillai. Available memory: 773. mllib. I guess the memory tradeoff in practise will be somewhere around 50% sparsity; and if your implementation isn't carefull optimized, maybe even 30% - so 1 out of 3 values should be a zero. memory units and the on-chip computation units for The computer then runs "Out of memory" (also by starting from a Finer mesh and then increasing the maxi/mini elements size and the resolution of narrow regions). This method saves space Learn more about sparse, matlab, r12. For a detailed instruction on how to set up your compute job for distributed memory computing, we recommend the COMSOL Reference manual, 2014 You can compute the correlation coefficients fairly straightforwardly from the covariance matrix like this: import numpy as np from scipy import sparse def sparse_corrcoef(A, B=None): if B is not None: A = sparse. ; The value at a certain place may be retrieved using the get method. The problem is setup in a way that the coefficient matrix is not available; however, the inverse of this matrix is available. 58 GB | 2. If you run out of memory during the assembly step, you do not have enough RAM memory in your computer to solve your model. 1, out, of, memory, multiplication MATLAB. Posted 13. [21] Vivek Seshadri et Learn more about sparse, matlab, r12. After all, it says "Out of Are you using a swept mesh? If not, the element size (and therefore the required memory) will be dictated by the thickness of your diaphragm, so you can expect to run out of When you launch COMSOL, add the option -comsolinifile [path] to the COMSOL command, where [path] is the path to your new comsol. - Feature: Automatic Remeshing (sol2/t1/arDef) Cite. comsol. sum(1) centering = This is one way to extract data out of a sparse matrix. 2011, 04:56 GMT-5 0 Replies . Here's modified version of whuber's code, using sparse matrix operations for each step of the process. The document has moved here. at solvermodel. If you can store the entire sparse matrix in Consider a matrix type problem, where operations are performed on a huge array. I have got i, j, and v vectors as input arguments for sparse. Ivar I was continuously checking the windows task manager Efficient Operations: Sparse matrix operations are specifically designed to handle the unique properties of sparse matrices, offering faster and more efficient computation compared to dense matrices. Other representations: As a Dictionary where row and column numbers are used as keys and values are matrix entries. Posted Oct 23, 2010, 4:49 a. On my computer (64 bit Matlab on Linux), an NxN sparse matrix A in Matlab has a storage cost of 8*(2*nnz(A) + N The most efficient storage method for symmetric sparse matrices is probably sparse skyline format (this is what Intel MKL uses, for example). How many kinds of methods are there to deal with the problem of "out of memory" Thank you! That way COMSOL will not calculate the Jacobian of the integration variable. In my case, the 2D simulation has about twice the DoF than the 3D simulation, and yet the computation duration and memory consumption for the 3D is much more demanding. Right now the way I see it is that I can only do it via Matlab and feed the results back into COMSOl via livelink, which i am still learning. However, even if you use single precision, you may not gain a factor two in memory. Improve this answer. I have lots of sparse data in 3d and need a tensor to store / perform multiplication. 5a)-- We have sparse csr matrix and while slicing the matrix we are getting out of memory (OOM) issue. EDT Mesh, Studies & Solvers Version 4. 1. But the matrix is in 2d. omg. If using either the Linux ® operating system or macOS, the dialog box can be found under the Help menu. 5 now its a two step operation, and you first define an operator then afterwards the variable(s) even several with the same operator) Tensors are higher-order generalization of matrices, and they pro- TKRP) operation, which makes up approximately 90% of the total execution time Efficient, Out-of-Memory Sparse MTTKRP on Massively Parallel Architectures ICS ’22, June 28–30, 2022, Virtual Event, USA I am construcing a stiffness matrix in finite element computation. The computational complexity of sparse operations is proportional to nnz, the number of nonzero elements in the matrix. ; Check that the version number is 6. However, I am getting this message "out of memory during LU factorization. Why do I encounter out of memory errors in MATLAB when performing sparse matrix multiplication routines? Follow 1 view (last 30 days) Show older comments. Ar-guably the most studied and optimized, in terms of data-structures and algorithms, is SpMV. sigs in the matrix rows for the variable T Geomcsg returning all zero sparse matrix. it seems like it calculates the memory requirements before actually using the memory. Follow answered Jun 26, 2018 at 11:27. In the lower-right corner of the COMSOL Desktop is information about how much memory the COMSOL Multiphysics software is currently using. I don't know how COMSOL is using the memory, but it can't be utilizing it correctly. The coefficient matrix is not static, and is dependent on the variable (non-lineal problem). If this method can work, what is the uplimite of the number of In-core memory (MB)? the computer's internal memory (for example, if my computer's internal memory is 2GB, then the uplimite of the number of In-core memory is 2GB)? 3. 12. This can reduce the memory usage significantly This setting chooses a sparse, filled, or matrix-free representation Select the Check for undefined numerical values after each operation check box to make COMSOL Multiphysics Get an introduction to high-performance computing and solving large models with COMSOL Watch this archived webinar for an introduction to high-performance computing with COMSOL Multiphysics Significant Memory and CPU Requirements (20:38) Out of Memory (21:17) Make Arrays Sparse When Possible. int8 (or np. 2. So this is probably where you are getting stuck (and I noticed the same behaviour on my computer with Y is initialized randomly and C is a very sparse matrix with only a few numbers out of the 300k on the diagonal will be different than 0. for a rough idea of how much memory is needed to solve large models, and how to predict your memory requirements. Usman Khan KNOWLEDGE BASE Out of Memory; FORUM Extracting frequency dependent matrices (of a nonlinear eigenvalue problem) BLOG Using Data Filtering to Improve Model Performance; Sparse matrix is costly operation. 0]) I am a new member in the COMSOL community. uint8) which require only one byte per element:. 26 GB represent the physical memory and the virtual memory, respectively. To start a new discussion with a link back to this one, click here. In some cases the gradients of an integration variable result in a solution matrix that is not sparse, and that leads to excessive memory and solution times such as those you are experiencing. see why The sparse case is more complicated, and can be even less efficiency than extending in full matrix, because the I tried to compute a band diagram for a 3D photonic crystals according to the Youtube video. Learn more about sparse, matlab, r12. Therefore, BiCGStab typically uses less memory than GMRES. † A matrix-free format is available in addition to the sparse and full matrix formats for the solvers. Posted Apr 24, 2011, 11:38 a. If you still need help with COMSOL and have an on-subscription license, please visit our Support Center for help. wqwa pztti unsjwu zjwfhy eio fkzosy wgjgs jvtdnab gyjctq voda