Share. It is currently written in a Single-Program-Multiple-Data style using explicit message passing for inter. Learning Objectives After you complete this tutorial, you should be able to: • Use Intel MKL routines for linear algebra • Compile and link your code • Measure performance using support functions • Understand the impact of threading on Intel MKL performance • Control threading for Intel MKL functions Collectives™ on Stack Overflow. I have at work. Even replacing CUBLAS with MAGMA BLAS did not help the GPU version to win out. so. Contact SIAM for additional information. The C++ prototype of this function is as follows: void pdgetrf_( int *m, // (global) The number of rows in the distributed matrix sub (A) int *n, // (global) The number of columns in the distributed matrix sub (A) // (local) Pointer into the local memory to an array of local size. The next important distinction among linear algebra problems is between the first two problems (solving Ax=b and least squares problems), and the last problem (computing eigenvalues and the SVD). Using OpenMPI + open source scalapack (v2. 4. ScaLAPACK additionally aims at scalability as the problem size and number of processors grows on distributed memory parallel machines. Connect and share knowledge within a single location that is structured and easy to search. You will need to add this subdirectory to the library search path of your compiler (typically via the LD_LIBRARY_PATH environment variable or the -L option to your compiler) and link to the library itself with -lcp2k. Connect and share knowledge within a single location that is structured and easy to search. and a symmetric matrix to tridiagonal form are consid ered in [ 11]. i. When I run the program, if I set the M and N variables, that is the number of rows and columns of the input matrix, the program will go all the way through, including a query of PDGESVD where I tell the program. a and other static library files to determine actual procedure names. Examples. This will create libcp2k. Share. Add a libraries setting to the Extension with all the libraries it requires. ScaLAPACK will run on any machine where both the BLAS and the BLACS are available. The first part of this paper presents the design of ScaLAPACK. 1 Introduction and Motivation LAPACK and ScaLAPACK are widely used software libraries for numerical lin-1 Answer. a in the relevant subdirectory of . so. a worstation which has 1TB RAM and 64 cores with 2 GPU RTX A6000 which gives 96GB. Q&A for work. 16. a -l:blacsF77init_MPI-LINUX-0. In this example we will read the input matrices from a file, distribute these matrices to the processes in the grid. ScaLAPACK depends on PBLAS operations in the same. To use the make file with the make include file, you use a VALET devrequire command to set and export the LDFLAGS and CPPFLAGS variable. a worstation which has 1TB RAM and 64 cores with 2 GPU RTX A6000 which gives 96GB. In ScaLAPACK, algorithms are presented in terms of processes, rather than physical processors. -lboost_regex-mt -lboost_unit_test_framework-mt -lboost_program_options-mt -lboost_thread-mt -lboost_regex-mt -lcurl -lxerces-c -ldb2 -lguide -lmkl_intel_lp64 . For scripts/ (those building Lapack first), we previously used our CMake wrapper of Lapack. Q&A for work. Instead of having an OpenMP #pragma parallel for parallelizing a loop for a multi-threaded CPU, OpenACCs #pragma acc kernels will turn the contained loops into kernel functions that are executed on the GPU. Different tasks can mean different input problem sizes or the same input problem. mpic++ cpp_scalapack_example. In order to perform computationally heavy calculations, we would require accessTuning ScaLAPACK for very large machines is even more important. Disabling the option "-Dscotch=OFF" would enable Mumps's internal reordering. It examines the building of the ship, life onboard during its maiden voyage, tragic decisions made that fateful night, the discovery ofScaLAPACK . {"payload":{"allShortcutsEnabled":false,"fileTree":{"MPI/scalapack":{"items":[{"name":"SLmake. Follow edited Sep 27, 2022 at 4:46. However, from running the example I linked to, the distribution seems to happen like the 2D right-up corner in your answer and it works with Cholesky's ScaLAPACK (I checked). All you need to include is only "cppscalapack. In order to use the functions in the library you will also. com documentation a simple example of matrix inversion with ScaLapack. 7. Stack Overflow | The World’s Largest Online Community for DevelopersIn Chapter 2, we presented an example program using ScaLAPACK. 0. com, or from the OEM or retailer. 0 Latest. Key design features are the use of distributed versions of the Level 3 BLAS as building blocks, and an object-oriented interface to the library routines. Reload to refresh your session. For example, consider distribution of rows. Show hidden characters. 0D+00 do j=1,n A(i,j) = (i+j)*j*1. age (LAPACK) and the Scalable Linear Algebra PACKage (ScaLAPACK), the combination of which is abbreviated Sca/LAPACK, aim to enhance and update these libraries for the ongoing revolution in processor. How to link with scalapack and impi correctly? Environment Ifort 11. DOI: 10. This article outlines the content and performance of some of the ScaLAPACK software. " GitHub is where people build software. This attempt seems to have died a while ago:poetry add scipy scikit-learn Share. Basic Workflow using ScaLAPACK. , make -s cc4s -j 4. Package libjlapack-java. do i=1,n x(i) = i*i*1. ScaLAPACK 2. Operations are performed on DistributedMatrix objects which can be easily created whilst hiding all the nasty details of block cyclic distribution. [petsc-users] installing petsc with scalapack from mkl. Like LAPACK, the ScaLAPACK routines are based on block. COSMA also contains a wrapper for ScaLAPACK pxgemm calls which offers scalapack interface (pxgemm functions with exactly the same signatures as ScaLAPACK). 1. Sorted by: 1. ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines. hpp This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. undefined symbol means a library included in headers is not linked to the shared object and that library's symbol cannot be found. For the larger projects where I use Scalapack with lengthy link commands, the transitive resolver in CMake would put the libraries out of order and fail to link. This tutorial will begin by reviewing the fundamental design principles of the BLAS and LAPACK and their influence on the development of ScaLAPACK. Gilbert, and X. On the cluster I'm using, where I compiled with impi and intel mkl, I lose 3648 MB with 16 tasks, and 7297 MB with 49 tasks. The Netlib lapack project's CMake has now matured to where our wrapper is no longer necessary, so we use Netlib Lapack directly in CMake scripts/ if user desires. On these machines, LINPACK and EISPACK are inefficient because their memory access patterns disregard the multi-layered memory hierarchies. ScaLAPACK solves dense and banded linear systems, least squares problems, eigenvalue problems, and singular value problems. g. Find centralized, trusted content and collaborate around the technologies you use most. Beginner 02-04-2011 09:26 AM. Every computer has a different set of linker flags depending on the package. In your main program you set. of Colorado Denver; and NAG Ltd. In this tutorial we learn how to install scalapack-mpich on CentOS 8. 2. Alternatively, you can link against an installation of Intel's oneAPI MKL library that provides all four. To demonstrate this functionality, here are two sample lists: numbers = [ 1, 2, 3] // python val numbers = List ( 1, 2, 3) // scala. You will learn how you can directly run LAPACKE from VS Studio (just C code, no Fortran!!!). inc4) gedit SLmake. Order code SE04. Teams. Host and manage packages Security. From my own experience, I think you should learn at least several standard routines in Lapack before you go to scalpack. As of May 2006, the latest distribution is scalapack-1. CPPScaLapack is a bunch of c++ header files. answered Sep 10, 2022 at 5:50. Assets 2. Matrices are laid out in a two-dimensional block-cyclic decomposition. Order code SE04. The reference functions are. Teams. With compilers that support it, the library can be compiled with long (8-byte) integers instead. I am confused that a call to the ScaLAPACK TOOLS routine SL_INIT initializes the process grid and routine Cblacs_gridinit( &ictxt, "Row", nprow, npcol ) is also for initializing a grid (I saw that in fortran sample code). If I use scalapack and pblas, and the code is run in serial (1x1 blacs process grid), how well does scalapack and pblas revert to the performance of lapack/blas? I am particularly interested in the. Presumably ilcm is from scalapack, not sure what the library name is. Matrices A and B are set to use a fixed block size. Resources. ScaLAPACK. pc file), but first the current version should at least build. Some anomalies in the old routine are. After a brief discussion of the BLAS and LAPACK, the block cyclic data layout, the BLACS, the PBLAS (Parallel BLAS), and the algo- rithms used are discussed. Untar the ScaLAPACK code: “tar xzf scalapack-1. These routines allow the factorization and solution of a dense system of linear equations via LU, QR, and Cholesky. It is a continuation of the LAPACK. Set the appropriate init parameter before calling MUMPS API in the linking test code. However, when it's odd, pdpotrf () thinks that the matrix is not positive. In theabsence of such a runtimesystem, ScaLAPACK assumes oneThe most commonly used API for distributed matrix multiplication is based on ScaLAPACK. 34b5e47. 2 to load ScaLAPACK version 2. Dynamics ScaLAPACK wrapper for Python. On my laptop it works fine with OpenMPI and directly searching for the default ScaLAPACK library: const libscalapack = Base. It is a library of high-performance linear algebra routines for distributed. 0 Kudos Copy link. There are packages for the shared libraries, for the static libraries and the development files (this one) and for test programs. 00D+00 end do end do and then simply multiply Matrix A by Vector x (b=Ax). CONCLUSIONS. 1-CMAKE folder in the source code folder. ScaLAPACK emerged. To be clear, I. Every computer has a different set of linker flags depending on the package. Community support is provided during standard business hours (Monday to Friday 7AM - 5PM PST). ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines. ScaLAPACK solves dense and banded linear systems, least squares problems, eigenvalue problems, and singular value problems, and is designed to be used in MPI-based parallel applications. It assumes matrices are laid. For Option (1) MKL works on. Connect and share knowledge within a single location that is structured and easy to search. Could you provide please a simple example which uses MPI and the Intel OneAPI routines of ScaLapack to invert large matrix. ScaLAPACK is a library of high performance linear algebra routines for distributed memory MIMD. New!!: Programming with Big Data in R and List of statistical packages · See more » Message Passing. NVPL ScaLAPACK. MPI) libraries • Run your code using the procedure required for the communication primitives library – It is at this stage that you set the number of processors your program will use • For the OSC T3E: module load scalapack f90 prog. Q&A for scientists using computers to solve scientific problems. example SLmake. 0. of California, Berkeley; Univ. do i=1,n x(i) = i*i*1. makefile. We'll provide a fix for this in a future update. ScalapackFx - Modern Fortran Interface for ScaLAPACK. It is a continu- ation of the LAPACK project, wlfich designed and produced analogous software for workstations, vector supercomputers, and shared memory parallel computers. When the matrix is distributed over many processors it takes less time and larger order matrices can be inverted. 0 %cce@14. Sparse array examples using MUMPS, Scalapack, BLACS, PARDISO with CMake - GitHub - scivision/sparse-fortran: Sparse array examples using MUMPS, Scalapack, BLACS, PARDISO with CMakeInstall scalapack from source 4. Copy link. The square block scattered decomposition is. During my self-learning process, I found that the best way to understand SCALAPACK is to first get a solid knowledge on LAPACK -- it's non-distributed version. Equation A Parallel MoM Code Using RWG Basis Functions and ScaLAPACK-Based In-Core and Out-. Reply. About us. 2 is compliant with 2. It can be used to solve linear systems, least squares problems, eigenvalue problems, and singular value problems. In ScaLAPACK, algorithms are presented in terms of processes, rather than physical processors. 2. ScaLAPACK then uses the PBLAS and BLACS to perform BLAS-like operations, but in a distributed SPMD fashion, which become a mix of communication between processes, and BLAS operations within the processes, more-or-less. Simple scalapack example routines written in C++. As an aid to achieving these goals the ScaLAPACK software has been designed to look as much like the LAPACK software as possible. Because the BLAS have proven to be very useful tools both within LAPACK. 1. Introduction. links ScaLAPACK LU with CUBLAS using a software em-ulation layer; This method exhibits worse performance than the existing ScaLAPACK LU using only CPUs because of the large data transfer latency overhead between the CPU and GPU. a. 6. scalapack. LAPACK and ScaLAPACK currently deal mostly with dense matrices, although some sparse matrix software is available, with more on the way. We unlock the potential of millions of people worldwide. Therefore, this is the approach we take in this tutorial. Description ScaLAPACK is an acronym for Scalable Linear Algebra Package or Scalable LAPACK. edu Department of Computer Science and Engineering University of California, Riverside Riverside, CA 92521 ABSTRACT It is well known that soft errors in linear algebra operations can be detected off-line at the end of the computation using. ) least squares. Problem: The row-major/column-major difference between both languages seems to be affecting my solution process. Consider appending hdf5 if you want to compile VASP with HDF5 support. ScaLAPACK is a library of routines for solving linear algebra problems on multiprocessor systems with distributed memory. In general, BLAS and BLACS are considered as the low-level components that needs to be optimized for different. Intel added ScaLAPACK support on OS X (MacOS) in 2015. It depends on the external libraries BLAS. in Computational Modeling (2019) @LNCC and, currently, Research Associate in the department of Mathematical and Statistical Sciences @CUDenver. LAPACK and ScaLAPACK are used to solve leadingMachine Learning Machine Learning Reinforcement Learning TensorBoard Containerized TensorFlow LAPACK and scaLAPACK# Documentation: LAPACK, scaLAPACK. It is a continuation of the LAPACK [3] project, which designed and produced analogous software for workstations, vector supercomputers, and. Create a symbolic link for every user 8. 0), my memory loss is much smaller (for example, ~7300 MB with intel, ~200 MB with openmpi), but my code runs significantly slower. Point to your CLAPACK-3. include, and append the path to the library libwannier. The original goal of the LAPACK project was to make the widely used EISPACK and LINPACK libraries run efficiently on shared-memory vector and parallel processors. hpp This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. In theabsence of such a runtimesystem, ScaLAPACK assumes oneYes I chose to omit the mkl_core and mkl_intel_lp64 from Scalapack_libraries to avoid link order issues. Click here to start Table of Contents ScaLAPACK Tutorial Outline Outline continued Introduction High-Performance Computing Today Growth of Microprocessor Performance Scalable Multiprocessors Performance Numbers on RISC Processors The Maturation of Highly Parallel Technology Architecture Alternatives Directions The printed version of the ScaLAPACK Users' Guide is available from SIAM. The MAGMA Sparse and MAGMA Batched packages have been included since MAGMA 1. edu Department of Computer Science and Engineering University of California, Riverside Riverside, CA 92521 ABSTRACT It is well known that soft errors in linear. scalapack-test-common is: ScaLAPACK is the parallel version of LAPACK used on clusters. h で宣言さ. The reference functions are. I would prefer to use impi/intel-mkl given how quickly that combination solves my problems. Give Intel your input on Intel® oneAPI Math Kernel Library to help make improvements to meet your needs: Take the Survey. It is available from netlib via anonymous ftp and the World Wide Web. The open-source version of ScaLAPACK is collaborative effort involving multiple institutions and individuals, and we would like to thank for their contributions: This product includes ScaLAPACK 2. I might be too obvious, but I have trouble building scalapack 2. Abstract. Hi, there: I am not sure which routine is to do the two-Dimensional Block Cyclic Data Distribution. Our implementation highly. The key ideas incorporated into ScaLAPACK include the use of. 1. I am interesting in applying a Cholesky factorization to a SPD huge matrix and then invert it. Everything works fine when the dimension of the SPD matrix is even. Python has a large number of Machine Learning and AI libraries, while Scala stands strong when it comes to big data processing. , MPICC). To allow a comparison to other libraries, parameters for the benchmark of the pgemm_ssb function are selected, such that the same operation can be expressed in a p?gemm call through a ScaLAPACK interface. Alexei_Yakovlev. Generated by. The values of LOCp() and LOCq() may be determined via a call to the ScaLAPACK tool function, NUMROC. Intel added ScaLAPACK support on OS X (MacOS) in 2015. 0, an open-source library under the modified BSD license and can be downloaded freely from Netlib (. In general there may be several processes on a processor, in which case we assume that the runtime system handles thescheduling of processes. ScalaPy is a Scala library developed by Shadaj Laddad. Cannot retrieve contributors at this time. mk file. It is a library of high-performance linear algebra routines for distributed memory message-passing MIMD computers and networks of workstations supporting parallel virtual machine (PVM) and/or message passing interface (MPI). linalg （在底层. See the relevant Packaging Guide section for an introduction. 6. This ScaLAPACK tutorial begins with a brief description of the LAPACK library. intel. For that reason, I would like to use MKL wi. Intel® Math Kernel Library (Intel® MKL) (Cluster) intel-mkl-doc. 0 folder. Scalapack with CMake enhancements to make Scalapack easier to use directly in other projects. Building with ScaLAPACK Given an n-by-n real/complex nonsymmetric matrix A, the Intel® MKL ScaLAPACK P?GEEVX expert drivers compute its: eigenvalues; left and/or right eigenvectors, optionally; balancing transformation to improve the conditioning of the eigenvalues and eigenvectors, optionally; reciprocal condition numbers for the eigenvalues, optionally. 0, released in February 2, 2022. ScaLAPACK can be found in the MKL. 6: If the location of the mpif90 command is part of your PATH env. /lib/. For usersSCALAPACK ¶ Scalable Linear Algebra PACKage. Your program with ScaLAPACK calls may be compiled with something like this: mpicxx -o your_binary_name -O2 your_source. a -L scalapack/. 1. ScaLAPACK solves dense and banded linear systems, least squares problems, eigenvalue problems, and singular value problems. It is a continuation of the LAPACK project, which. Sc. Then you can go to mkl install folder/example directory to find Scalapack sample code to see if you can build and run the them. Test siesta 7. The ScaLAPACK and LAPACK development is mostly driven by algorithm research, the result of the user/vendor survey, the demands and opportunities of new architectures and programming languages, and the enthusiastic partici-pation of the research community in developing and ofiering improved versionsThough OpenBLAS was built successfully, it said at the end that I should use OMP_NUM_THREADS since I used USE_OPENMP=1. After going to all possible "Introductions" to ScaLapack, I still can't understand how to carry out a simple PDGEMV operation using it. Figure 2 shows the performance of ScaLAPACK PZGETRF for factoring a complex*16 matrix with N = 40, 000 on 180 MPI tasks spawned over fifteen nodes (twelve tasks per node, or one task associated. Could you tell me please what do I do wrong (I am new with ScaLAPACK)? Thank you and best wishes. Compare. You can use module spider scalapack to view available modules. SLATE will deliver fundamental dense linear algebra capabilities for current and upcoming distributed-memory systems, including GPU-accelerated systems as well as more traditional multi core-only systems. List of statistical packages. In general there may be several processes on a processor, in which case we assume that the runtime system handles thescheduling of processes. New re-designed algorithm for double precision LU Factorization. Matrices should bestoredas 1d array (A [ i + lda*j ], not A) To invoke ScaLAPACK routines in your. Some of the largest machines will likely be heterogeneous in performance, if only because they are shared resources. 2. 04. ScaLAPACK 2. Libdl. I have at work. Improve this answer. 在上一篇中我们非常简要地介绍了 ScaLAPACK 软件。 虽然 ScaLAPACK 在设计上作了很多工作使其方法接口与 LAPACK 尽量保持一致，但是直接使用 Fortran 或 C 语言按照上一篇中介绍的步骤使用 ScaLAPACK 仍然是一件比较麻烦和容易出错的事情，就好比我们使用 numpy. When I do: mpif77 example1. Click here to start Table of Contents ScaLAPACK Tutorial Outline Outline continued Introduction High-Performance Computing Today Growth of Microprocessor. ScaLAPACK has been tested on MPPs like the IBM SP series, Cray T3E, and SGI Origin 2000/3000, and tested on clusters of PCs and networks of workstations supporting MPI or PVM. 9780898719642 Corpus ID: 59805161; ScaLAPACK Users' Guide @inproceedings{Blackford1987ScaLAPACKUG, title={ScaLAPACK Users' Guide}, author={L. The new routine is both faster and more reliable than the old one, and contains some new features such as aggressive early deation to improve the performance. Release 2. I have the chance to use many computers for that purpose, thus I am only interested in distributed solutions. a -l:blacs_MPI-LINUX-0. Also included: - PBLAS, Parallel Basic Linear Algebra Subprograms - BLACS, Basic Linear Algebra. libMBD is included in FHI-aims, Quantum Espresso, DFTB+, and ESL. 4k 37 37 gold badges 152 152 silver badges 186 186 bronze badges. 2. But if this happens during many bands step of single shot GW (G0W0), then changing ALGO is not possible as for this step exact diagonalization is needed. While it is simple to use, it may not provide optimal. Our assessments, publications and research spread knowledge, spark enquiry and aid understanding around the world. cpp -o cpp_mpi_scalapack -L/opt/scalapack/lib/ -lscalapack -L/opt/atlas/lib/ -llapack -lf77blas -lcblas -latlas -lgfortran In ScaLAPACK, algorithms are presented in terms of processes, rather than physical processors. Here my makefile and the ScaLapack example: enter link description here. What is scalapack-mpich. I have seen similar things for C++ or Python. 1) Use some grid tool to create virtual supercomputer from networked desktops and LAPACK functions from MKL (does LAPACK scale automaticly code to n processors/cores ? ) 2) Use cluster created from networked desktops and ScaLAPACK functions with MPI. The programs solve commonly occurring problems in dense linear. To associate your repository with the lapack topic, visit your repo's landing page and select "manage topics. FT-ScaLAPACK: Correcting Soft Errors On-Line for ScaLAPACK Cholesky, QR, and LU Factorization Routines Panruo Wu [email protected] matrix should be distributed correctly. Found 27 matching packages. Discuss (0) There are three main ways to accelerate GPU applications: compiler directives, programming languages, and preprogrammed libraries. New in NWChem 6. We unlock the potential of millions of people worldwide. The importance of block-partitioned algorithms in reducing the frequency of data movement between different levels of hierarchical memory is stressed. algebra routines for distributed memory computers supporting MPI. It lets us use any Python libraries from a Scala program. Fund open source developers. 2. ". Spack sets up several environment variables like PATH by default to aid in building a package, but many packages make use of environment variables which convey specific information about their dependencies (e. I am a student and this is my first time using MKL. 3. You signed in with another tab or window. 7 of ScaLAPACK. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn,. org. SLATE will provide coverage of existing LAPACK and ScaLAPACK functionality, including parallel implementations of Basic Linear Algebra. 3 Zoom in: Dense Linear Algebra + FFT LAPACK FFT LU/QR ScaLAPACK CPU support only DPC++/OpenMP offload with GPU support BLAS Level 1. In Chapter 2, we presented an example program using ScaLAPACK. or if you want to activate always the silent mode you can write in your config. e. It can be used to solve linear systems, least squares problems, eigenvalue problems, and singular value problems. ScaLAPACK: Scalable LAPACK Each ScaLAPACK routine has a LAPACK equivalent Naming scheme: LAPACK name preceded by a ‘P’ 4 basic steps required to call a ScaLAPACK routine Initialize the process grid Distribute matrices on the process grid Call the ScaLAPACK routine Release the process grid. Install gcc, OpenMPI and OpenMP using homebrew. In this example we will read the input matrices from a file, distribute these matrices to the processes in. Dynamic Linking. The importance of developing standards for computational and message passing interfaces is discussed. Li. I know there is a C interface. The key ideas incorporated into ScaLAPACK include the use of In this tutorial we learn how to install scalapack-test-common on Ubuntu 20. Here's the system I intend to solve: I didn't find on inte. As of version 2. Subscribe to RSS Feed; Mark Topic as New; Mark Topic as Read; Float this Topic for Current User;ScaLAPACK software is multi-layered, enabling it to be portable and efficient. Du et al. To accomplish these goals we are also relying on bet-ter software engineering techniques and contributions from collaborators at many institutions. The fundamental design principles of the BLAS and LAPACK are reviewed, followed by a discussion of the underlying building blocks of ScaLAPACK, the BLACS and the PBLAS, and the contents of the ScalAPACK library are enumerated. 0) routine PDLAHQR. 60; the cost for nonmembers is $49. By default, the about to be released GCC 10 is more strict about Fortran argument types. 6. 20). edu Zizhong Chen chen@cs. Compare. mkl_core_dll. Sparse Solver Routines x. The open source library ScalapackFx provides convenient modern Fortran (Fortran 2003) wrappers for the routines of the ScaLAPACK library. 50. ScaLAPACK routines to reduce a real 1-!en eral matrix to Hessenberg or bidiagonal form. They are implemented using a block cyclic data distribution, and are built using de facto standard kernels for matrix and vector. inc","contentType":"file"},{"name. Fix argument mismatches for implicitly defined functions (for gcc-10+ compatibility), PR #26. Aug 24, 2022. Collectives™ on Stack Overflow. What is scalapack-doc. It is a library of high-performance linear algebra routines for distributed memory message.