Cusparse python

Cusparse python. May 4, 2018 · __OS Information__ Platform : Windows-10-10. scipy. r. cuSolverRF At this point CSR routines from cuSPARSE are the only functions with higher-level python wrappers and tests. As such, nvidia-cusparse-cu12 popularity was classified as an influential project. CuPy, CUDA cuSPARSE, and OpenMP are included in the context of Sparse Deep Neural Network (SpDNN) implementations (derived from the Graph Challenge reference serial code in MATLAB) and the performance results were produced using single and multiple GPUs from NVIDIA DGX-A100 40GB Links for nvidia-cusparse-cu11 nvidia_cusparse_cu11-11. Operations between a dense matrix and a sparse vector: multiplication. scsrgeam2_buffer_size_ext (intptr_t handle, int m, int n, intptr_t alpha, intptr_t descr_a, int nnz_a, intptr_t csr_sorted_val_a, intptr_t csr_sorted_row_ptr_a, intptr_t csr_sorted_col_ind_a, intptr_t beta, intptr_t descr_b, int nnz_b, intptr_t csr_sorted_val_b, intptr_t csr_sorted_row_ptr_b, intptr_t csr_sorted_col Nov 4, 2013 · Pysparse is a fast sparse matrix library for Python. Donate today! Mar 19, 2021 · cuSPARSE SpMM. May 20, 2021 · The cuSPARSE library functions are available for data types float, double, cuComplex, and cuDoubleComplex. cuda. This article explores One possibility to solve general sparse linear systems in CUDA is using cuSOLVER. ” I tried typing it in Python code and the Anaconda prompt and it didn’t work. py","path":"examples/stream/cublas. It appears that PyTorch 2. With it, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and supercomputers. Documentation is located here May 2, 2023 · The python package nvidia-cusparse-cu12 receives a total of 2,719,098 weekly downloads. I am developing an optimization of the solver for which it would be important for me to know if CUSPARSE implements the SpMV product in its scalar version or in the vector one, or if it is any other variant (https create (). - yghdd/cusparse-python Aug 6, 2019 · However, this is one of the few cuSparse operations that doesn't support an optional built-in transpose for the input matrix. See cusparseGetVersion. Contribute to lebedov/scikit-cuda development by creating an account on GitHub. 9 approaching its release, many are curious about t the potential for Python 4. 9 MB view hashes ) Uploaded Aug 17, 2024 Python 3 Sep 23, 2020 · The cuSPARSE library functions are available for data types float, double, cuComplex, and cuDoubleComplex. Python interface to the sparse matrix vector multiplication functionality of NVIDIA's cuSPARSE library. May 8, 2015 · Recently when I used cuSparse and cuBLAS in CUDA TOOLKIT 6. com cuSPARSE Release Notes: cuda-toolkit-release-notes Oct 18, 2023 · Python 3. sparse python module. 2u1 GraphBLAST Jan 28, 2021 If you already have the Anaconda free Python distribution, take the following steps to install Pyculib: Run the command conda update conda. Thus the package was deemed as safe to use. Jun 27, 2023 · It seems like the CuSparse ". CPU Model: >wmic cpu get caption, deviceid, name, numberofcores, maxclockspeed, status Caption DeviceID MaxClockSpeed Name NumberOfCores Status cuSPARSE vs. 3. cuSPARSE. 11. com, we hope that we can solve our problem directly with you developers here. collect_env to detect the inconsistency of CUDA versions? If there is inconsistency, you need to install a different build of PyTorch to match Studio Lab CUDA version. 0] on linux Type "help", "copyright", "credits" or "license" for more information. Routines are backed by CUDA libraries (cuBLAS, cuFFT, cuSPARSE, cuSOLVER, cuRAND), Thrust, CUB, and cuTENSOR to provide the best performance. Re-installing CUDA does not solve anything. The full source code is hosted in the NVIDIA/nvmath-python repository. Making the Most of Structured Sparsity in the NVIDIA Ampere Architecture. On devices where the L1 cache and shared memory use the same hardware resources, this returns through pCacheConfig the preferred cache configuration for the current device. cuSPARSE host APIs provide GPU accelerated basic linear algebra routines, and cuSPARSELt host APIs provide structured sparsity support that leverages sparse tensor cores for GEMM. See NVIDIA cuBLAS. 6. Cusp provides a flexible, high-level interface for manipulating sparse matrices and solving sparse linear systems. CuPy is an open-source array library for GPU-accelerated computing with Python. Compute the following multiplication: In this operation, A is a sparse matrix of size MxK, while B and C are dense matrices of size KxN MxN, respectively. See cusparseCreate. Using different versions Jun 16, 2019 · Anyway, both cython and python ctypes allow you to access C-callable libraries from python. I tried to do that by following the instructions from here f&hellip; cuSolver库是一个以cuBLAS&cuSPARSE库为基础的高级包，将三个库囊括在一起，可以独立使用或配合使用。cuSolver，可以实现类似lapack的功能，如j普通矩阵的分解，稠密矩阵的三角解法，稀疏矩阵的最小二乘解法，本征值解法。 1. whl Oct 3, 2022 · Uploaded Oct 3, 2022 Python 3 Windows x86-64 nvidia_cusolver_cu11-11. Apr 17, 2019 · It's caused by missing the cusparse. If you need to use a particular CUDA version (say 12. cuSolverSP. 2), which has a better average CUSPARSE (CUDA Sparse Matrix) provides linear algebra subroutines used for sparse matrix calculations. May 28, 2015 · Dear NVIDIA community, since we were not very successful yet posting this problem on stackoverflow. These matrices have the same interfaces of SciPy’s sparse matrices. If you do not have Anaconda installed, see Downloads. Feb 20, 2020 · For the record, this happens on a pre-built Paperspace Gradient environment with CUDA/cuDNN pre-installed. Pycuda is one of the more pythonic way to handle cuda in python as @nluigi suggested. gz Complete output from command python setup. CuPy utilizes CUDA Toolkit libraries including cuBLAS, cuRAND, cuSOLVER, cuSPARSE, cuFFT, cuDNN and NCCL to make full use of the GPU architecture. 75-py3-none-manylinux2014_x86_64. It is implemented on top of the NVIDIA® CUDA™ runtime (which is part of the CUDA Toolkit) and is designed to be called from C and C++. The GPU I used is NVIDIA Titan Black. In the sparse matrix, half of the total elements are zero. That means, SciPy functions cannot take cupyx. Overall, the Python/CUDA ecosystem still seems weirdly fractured, with no obvious choice existing for many common tasks. com cuSPARSE Release Notes: cuda-toolkit-release-notes 代码实现完整，优化度高，性能也是同平台下无敌。Sputnik在CUDA Core上实现，基于CSR(Compressed Sparse Row)压缩格式完成了非结构化稀疏矩阵乘，解决了cuSPARSE等稀疏矩阵库(当时的)针对高稀疏度的局限性，如图1。 nvmath-python Bindings; cuSPARSE (nvmath. dev5. The library targets matrices with a number of (structural) zero elements which represent > 95% of the total entries. It is implemented on NVIDIA CUDA runtime, and is designed to be called from C and C++. py egg_info: cc1plus: warning: command line option '-Wstrict-prototypes' is valid Contents . 6-py3-none-manylinux2014_x86_64. See Dec 8, 2020 · He primarily works on the cuSPARSE and cuSPARSELt libraries, focusing on new features and performance optimization. ANACONDA. destroy (intptr_t handle). Each of these can be used independently or in concert with other toolkit libraries. As illustrated below, the COO format may also be used to efficiently construct arrays. New Generic API provides ~5x performance improvement NVIDIA A100@1095,1215GHz cuSPARSE CUDA 11. bindings. The cuSPARSELt APIs allow flexibility in the algorithm/operation selection, epilogue, and matrix characteristics, including memory layout, alignment, and data types. Warnings issued by CHOLMOD are converted into Python warnings of type CholmodWarning. 86. PyTorch currently supports COO, CSR, CSC, BSR, and BSC. See NVIDIA cuSPARSE for an in-depth description of the cuSPARSE library and its methods and data types. The contents of the programming guide to the CUDA model and interface. 10. The cuSPARSE library provides cusparseSpMM routine for SpMM operations. We also have a prototype implementation to support :ref: semi-structured sparsity<sparse-semi-structured-docs>. Using different versions of the cusparse. utils. 6 Python Locale : en_GB cp1252 __LLVM information__ LLVM May 26, 2015 · I'm trying to interface the sparse cuSOLVER routine cusolverSpDcsrlsvqr() (>= CUDA 7. dn_mat_get_values; View page source Feb 22, 2022 · @saidineshpola Thank you for trying to use Studio Lab. In my simple code, the function cusparseSnnz returns the status 6 which is CUSPARSE_STATUS_INTERNAL_ERROR. Using different versions If you need a slim installation (without also getting CUDA dependencies installed), you can do conda install -c conda-forge cupy-core. 39s), in contradiction with NVIDIA’s reports that CUSPARSE is several times faster than Dec 31, 2019 · Pipenv might be a better choice for managing multiple Python environments. If you had a zero-based matrix from an external library, you can tell CUSPARSE using 'Z'. The cuBLAS binding provides an interface that accepts NumPy arrays and Numba’s CUDA device arrays. The sparse Level 1, Level 2, and Level 3 functions follow this naming convention: cuSPARSELt 0. 1. CuPy supports sparse matrices using cuSPARSE. cuSPARSE is not guaranteed to be backward compatible at the binary level. Jun 16, 2019 · Anyway, both cython and python ctypes allow you to access C-callable libraries from python. In terms of CUDA Toolkit (CTK) choices, nvmath-python is designed and implemented to allow building and running against 1. cuBLAS¶. This page contains the API reference information. *_matrix and scipy. For other modes, the user has to transpose A or B explicitly. 3. CholmodTypeConversionWarning¶ CHOLMOD itself supports matrices in CSC form with 32-bit integer indices and ‘double’ precision floats (64-bits, or 128-bits total for complex numbers). However this code snippet use driver version to determine the cusparse Jul 26, 2017 · Pyculib provides Python bindings to the following CUDA libraries: cuBLAS; cuFFT; cuSPARSE; cuRAND; CUDA Sorting algorithms from the CUB and Modern GPU libraries. Therefore, we decided to Jun 2, 2017 · The cuSPARSE library contains a set of basic linear algebra subroutines used for handling sparse matrices. There is a Python wrapper for it here. 1 day ago · Tutorial. See the full health analysis review. cuSolverDN . 9 MB view hashes ) Uploaded Aug 5, 2024 Python 3 Jun 25, 2018 · You would issue that command in python, before you import numba or pyculib. 五六年前深度学习还是个新鲜事的时候，linux下显卡驱动、CUDA的很容易把小白折磨的非常痛苦，以至于当时还有一个叫manjaro的发行版，因为驱动安装简单流行。老黄也意识到了这个问题，增加了很多新的安装方式。 最…. 3-py3-none-win_amd64. The general format of a CSR sparse matrix representation is documented in many places, including the CUSPARSE manual. The argparse module makes it easy to write user-friendly command-line interfaces. Sep 29, 2015 · You can convert a dense matrix to sparse with code you write yourself. So my guess is that you've upgraded your CUDA version but somehow forgot to upgrade the CuSparse library ? Actually, I think this is because my cuda toolkit version is not the same as GPU driver. 0. nvmath-python (Beta) is an open source library that provides high-performance access to the core mathematical operations in the NVIDIA math libraries. Click on the green buttons that describe your target platform. sparse). The sparse Level 1, Level 2, and Level 3 functions follow this naming convention: NVIDIA Math Libraries in Python. The lil_array class supports basic slicing and fancy indexing with a similar syntax to NumPy arrays. Provides basic linear algebra building blocks. 0), you can use the cuda-version metapackage to select the version, e. t. Dec 16, 2016 · Hi, I am having issues making a sparse matrix multiplication work fast using CUSPARSE on a linux server. GraphBLAST •GPU implementation of Sparse Matrix –Dense Matrix Multiplication (SpMM) is not currently available in GraphBLAST •Sparse Matrix –Sparse Matrix Multiplication (SpGEMM) uses cuSPARSE old APIs. Oct 5, 2012 · I am trying to get familiar to the cuSparse library. 4. This github repository is the codebase of the GraphChallengePNNL 2022 using Python and C/C++ programming models. Feb 27, 2020 · In the documentation of cuSparse, it stated that the function cusparseXcoo2csr. dll" has to be compatible with the CUDA version. where refers to in-place operations such as transpose/non-transpose, and are scalars. Learn more Explore Teams Feb 15, 2018 · Tried to install via pip install cupy but got the following error: Collecting cupy Using cached cupy-2. h header file and shared library is not supported. I move the directory cuda into another directory. 17763 OS specific info : 1010. Here is an example using python ctypes of calling compiled routines that use a CUDA library. GitHub Gist: instantly share code, notes, and snippets. 48-py3-none-manylinux2014_x86_64. GPU library APIs for sparse computation. In the solver, the SpMV product is used many times. cholmod. 0 is a topic of great anticipation and speculation within the tech community. py. Python interface to GPU-powered libraries. whl (572. whl; Algorithm Hash digest; SHA256: bfa07cb86edfd6112dbead189c182a924fd9cb3e48ae117b1ac4cd3084078bc0 cuSPARSE - GPU-accelerated BLAS for sparse matrices; cuSPARSELt - Lightweight GPU-accelerated BLAS for sparse matrices; cuTENSOR - GPU-accelerated tensor linear algebra library; cuTENSORMg - Multi-GPU GPU-accelerated tensor linear algebra library; NPP - Provides GPU-accelerated image, video, and signal processing functions In other words, if a program uses cuSPARSE, it should continue to compile and work correctly with newer versions of cuSPARSE without source code changes. class sksparse. Julia uses one-based indexing for arrays, but many other libraries (for instance, C-based libraries) use zero-based. 91-py3-none-manylinux1_x86_64. *_matrix objects as inputs, and vice versa. CPU sparse solver in Python. CUDA Library Samples. 0 have been compiled against CUDA 12. Federico holds a PhD in computer science and his background is in graph algorithms and sparse computation for GPU architectures. can also be used to convert the array containing the uncompressed column indices (corresponding to COO format) into an array of column pointers (corresponding to CSC format) cuSPARSE Library Documentation The cuSPARSE Library contains a set of basic linear algebra subroutines used for handling sparse matrices. conda install -c conda-forge cupy cuda-version=12. 5. These bindings are direct ports of those available in Anaconda Accelerate. Enabling GPU-accelerated math operations for the Python ecosystem. Did you try python -m detectron2. nvmath. whl nvidia_cusparse_cu11-11. 结论： 1、先单独看cusparse的表现，库里面会调用两个kernel，分别是binary_seach和load_balance。这个名称简写了。总之，就是cusparse不管来的数据是啥，都会进行负载均衡，在数据量比较多的时候，额外的开销比较少，能够取到足够的效益。 The NVIDIA® CUDA® Toolkit provides a development environment for creating high-performance, GPU-accelerated applications. cuSOLVER has three useful routines:. Previous Next In Python, distributed frameworks typically use the cloudpickle library, an enhanced version of the Python pickle module, to convert objects, including functions, into a stream of bytes. The problem is I couldn't find a function in cuSparse that can perform a May 21, 2015 · I think the most used libraries for sparse matrix operations using CUDA is cuSPARSE, which already comes included in the CUDA toolkit and supports all common sparse matrix formats. For the CSR (compressed-sparse-row) formulation, you could also use the CUSPARSE function for this. nvmath-python. It also implements a number of iterative solvers, preconditioners, and interfaces to efficient factorization packages. Consequently, I decided to try linking it by setting an environment variable: The cuSolver library is a high-level package based on the cuBLAS and cuSPARSE libraries. The runtime I get for a X^T*X calculation for X of size (678451, 1098) with accelerate is 30 times that of scipy (11. [url]c++ - CUDA shared memory issue (and using CUDA with python/ctypes) - Stack Overflow. Learn More Now available on Stack Overflow for Teams! AI features where you work: search, IDE, and chat. 86-py3-none-manylinux1_x86_64. 5 to do sparse matrix multiplication, I find cuSPARSE is much slower than cuBLAS in all cases! In all my experiments, I used cusparseScsrmm in cuSparse and cublasSgemm in cuBLAS. e. Conversion to/from SciPy sparse matrices# cupyx. create (). Nov 28, 2022 · CUDA vs. nvidia-cusparse-cu11 11. Jun 20, 2024 · CUSPARSE_SPMM_COO_ALG4 and CUSPARSE_SPMM_CSR_ALG2 should be used with row-major layout, while CUSPARSE_SPMM_COO_ALG1, CUSPARSE_SPMM_COO_ALG2, CUSPARSE_SPMM_COO_ALG3, and CUSPARSE_SPMM_CSR_ALG1 with column-major layout. Only the NN version is supported. cusparse)nvmath. Pyculib provides Python bindings to the following CUDA libraries: cuBLAS; cuFFT; cuSPARSE; cuRAND; CUDA Sorting algorithms from the CUB and Modern GPU libraries. get_version (intptr_t handle). What is CUSP? Cusp is a library for sparse linear algebra and graph computations based on Thrust. Install nvmath-python¶ nvmath-python, like most modern Python packages, provides pre-built binaries (wheels and later conda packages) to the end users. The python package nvidia-cusparse-cu116 was scanned for known vulnerabilities and missing license, and no issues were found. When we were working on our "Large Steps in Inverse Rendering of Geometry" paper , we found it quite challenging to hook up an existing sparse linear solver to our pipeline, and we managed to do so by adding dependencies on large projects (i. If you are open to call C/C++ code inside python there is also CUSP:. Jun 14, 2022 · Hi all, I am using CUSPARSE to implement the Preconditioned Conjugate Gradient. *_matrix are not implicitly convertible to each other. For beta!= 1, most algorithms scale the output matrix before the main computation. cupyx. About Us Anaconda Cloud Download Anaconda CUSPARSE allows us to use one- or zero-based indexing. CUDA 12. It provides several sparse matrix storage formats and conversion methods. 23 Required dependencies: nvidia-nvjitlink-cu12 Jun 21, 2023 · I downloaded the Isaac ROS docker image on my Orin Nano, and I want to install the package YOLOv5-with-Isaac-ROS, for that I need to first install torchvision. It consists of two modules corresponding to two sets of API: The cuSolver API on a single GPU. NOTE: Pyculib can also be installed into your own non-Anaconda Python environment via pip or setuptools. 66s vs 0. By data scientists, for data scientists. Conversion to/from SciPy sparse matrices¶. And, of course, ask for help if something is being done incorrectly in order to improve performance. Nov 16, 2022 · Hashes for nvidia_cusparse_cu12-12. x and 2. cusparse. 2 Downloads Select Target Platform. Only supported platforms will be shown. In other words, if a program uses cuSPARSE, it should continue to compile and work correctly with newer versions of cuSPARSE without source code changes. 2 MB view hashes ) Uploaded Aug 17, 2024 Python 3 Aug 5, 2024 · Uploaded Aug 5, 2024 Python 3 Windows x86-64 nvidia_cudnn_cu11-9. Run the command conda install pyculib. cudaDeviceGetCacheConfig # Returns the preferred cache configuration for the current device. h in cuda directory. sparse. get_property (int type). py","contentType":"file"},{"name Feb 28, 2018 · As pointed out in comments, NVIDIA ship the cuSPARSE library which includes functions for sparse matrix products with dense vectors. tar. whl (417. cudart. 17763-SP0 Release : 10 System Name : Windows Version : 10. 0) using PyCUDA and am facing some difficulties: I have tried wrapping the methods the same way the dense cuSolver {"payload":{"allShortcutsEnabled":false,"fileTree":{"examples/stream":{"items":[{"name":"cublas. Visit the popularity section on Snyk Advisor to see the full health analysis. sgtsv2_buffer_size_ext (intptr_t handle, int m, int n, intptr_t dl, intptr_t d, intptr_t du, intptr_t b, int ldb) → size_t [source] ¶ See cusparseSgtsv2_bufferSizeExt . whl (128. Alternatively, if you’re using ActiveState Python, you can use our package management tool (State Tool) to uninstall Python packages by running the following command: state uninstall <packagename> Watch the video on how to uninstall Python packages using the State Tool. It is also possible to easily implement custom CUDA kernels that work with ndarray using: Kernel Templates: Quickly define element-wise and reduction operation as a single CUDA kernel Summary: CUSPARSE native runtime libraries Latest version: 12. cuSPARSE¶ Provides basic linear algebra operations for sparse matrices. There's a line in the documentation that said . This document has been moved to Sparse matrices (cupyx. With Python 3. Yes, it is not cusparse, but the methodology would be similar. For a more gentle introduction to Python command-line parsing, have a look at the argparse tutorial. 17763SP0Multiprocessor Free __Python Information__ Python Compiler : MSC v. For n == 1, the routine may use cusparseSpMV() Nov 10, 2022 · The future of Python 4. (c++ - Solving sparse definite positive linear systems in CUDA - Stack Overflow) We are experiencing problems while using cuSOLVER’s cusolverSpScsrlsvchol function, probably due to misunderstanding of the cuSOLVER nvmath. No official documentation exists, but there is a short example below and more can be seen in the functions in tests/test_cusparse. Contribute to NVIDIA/CUDALibrarySamples development by creating an account on GitHub. Jan 12, 2022 · op (a) = a if trans == cusparse_operation_non_transpose a t if trans == cusparse_operation_transpose a h if trans == cusparse_operation_conjugate_transpose The block in BSR format is of size blockDim*blockDim , stored as column-major or row-major as determined by parameter dirA , which is either CUSPARSE_DIRECTION_COLUMN or CUSPARSE_DIRECTION_ROW . Follow @fedebusato on Twitter Oct 18, 2022 · Uploaded Oct 18, 2022 Python 3 Windows x86-64 nvidia_cublas_cu11-11. Cusp is a library for sparse linear algebra and graph computations based on Thrust. 13 (main, Aug 25 2023, 13:20:03) [GCC 9. g. CUSOLVER It combines three separate libraries under a single umbrella, each of which can be used independently or in concert with other toolkit libraries. 2. In my case, it was apparently due to a compatibility issue w. See cusparseDestroy. 7. These bytes can be sent from the client, where the function was input by the user, to remote worker processes, where they are turned back into executable cuSPARSE - Basic Linear Algebra for Sparse Matrices on NVIDIA GPUs. Provide Feedback: Math-Libs-Feedback@nvidia. cusparse and scikit-sparse), only to use a small part of its functionality. gz; Algorithm Developed and maintained by the Python community, for the Python community. Numba now has Python bindings for the cuSparse library via the pyculib package. . The cuSPARSE library contains a set of basic linear algebra subroutines used for handling sparse matrices. cusolverSpDcsrlsvlu, which works for square linear systems (number of unknowns equal to the number of equations) and internally uses sparse LU factorization with partial pivoting; To construct an array efficiently, use either dok_array or lil_array. The library routines provide the following functionalities: Operations between a sparse vector and a dense vector: sum, dot product, scatter, gather. Apr 23, 2021 · Hashes for nvidia-cusparse-0. Nov 16, 2019 · To answer the question how naive described implementation really is I’ve compared it with the NVIDIA CUDA Sparse Matrix library (cuSPARSE) CSR implementation (tab. >>> import torch Traceback Oct 18, 2023 · I've also had this problem. The 'O's tell CUSPARSE that our matrices are one-based. Guido van Rossum, the creator of Python, offers exclusive insights into what might lie ahead for this popular programming language. White paper describing how to use the cuSPARSE and cuBLAS libraries to achieve a 2x speedup over CPU in the incomplete-LU and Cholesky preconditioned iterative methods. See Dec 15, 2023 · I wanted to report and ask for help when using CUDA cuSolver/cuSparse GPU routines that are slower than CPU versions (Python → Scipy Sparse Solvers). 与cusparse的性能对比. The cuSolverMG API on a single node multiGPU. 1900 64 bit (AMD64) Python Implementation : CPython Python Version : 3. 0 that I was using. Released: Oct 18, 2022. 2. 1 so they won't work with CUDA 12. The figure shows CuPy speedup over NumPy. Initially, I was calling CUSPARSE via the accelerate. I’m not sure I understand what you mean by “issue that command in python. I get into the directory /user/local/ and find 2 cuda directory: cuda and cuda-9. 0 and they use new symbols introduced in 12. I think the CUDA driver and cuSparse Nov 3, 2014 · cusparseとは、cuda用の疎行列計算ライブラリです。 使い方は ドキュメント を見てもらうのが一番早い気がしますが、私は若干つまづいたので、ここに「疎行列×ベクトル」の演算を実行するまでの簡単なチュートリアルっぽいことを書きます。 May 30, 2018 · Exception: Cannot open library for cusparse: library cusparse not found Googling a little, I think that it is because the cuSPARSE library is not linked to my Python application. vkjuz fasaw qjmmi uhrxq cwksn qxky eeliwl ypse varfbjb cumwz