May 19, 2019 Mac BLAS. GitHub Gist: instantly share code, notes, and snippets. Parallel BLAS in R. Which is a large library that includes an optimized BLAS library for Intel chips. This optimized BLAS, in addition to being optimized with respect to the code itself, is designed to be multi-threaded so that it can split work off into chunks and run them in parallel on multi-core machines. Besides Accelerate (Mac.
Last update: Mon Sep 22 18:34:37 2003
| Comments, and reports of errata or bugs, are welcome via e-mail to the author, Nelson H. F. Beebe <beebe@math.utah.edu>. In your report, please supply the full document URL, and the title and Last update time stamp recorded near the top of the document. |
Table of contents
Documentation for LAPACK
There is locally-provided online documentation for LAPACK inside the GNU Emacs info system. In emacs, type C-h i to enter the info system, then type MLocal and MLAPACK. You can do the same thing in the standalone xinfo viewer. That documentation is also available in HTML form for Web browsers.
The standard reference manual for LAPACK has appeared in three editions:
Linking with locally-installed libraries
Because of the problems documented below in using vendor-provided LAPACK libraries, LAPACK and its associated BLAS (Basic Linear Algebra Subroutines) library have been installed separately on all local systems, so that Fortran code can be (almost) uniformly linked like this:
f77 can be replaced by g77, f90, f95, fort, pgf77, pgf90, pghpf, xlf, xlf90, xlf90_r , xlf90_r7, xlf95, xlf95_r, xlf95_r7, xlf_r, or xlf_r7, where available.
The C version of LAPACK, CLAPACK, which is produced automatically from the Fortran sources by the f2c translator, is also available, allowing C code to be linked like this:
The -lctmg library may not be needed. Although the code is in C, the internals behave like Fortran with respect to calling conventions, array storage order, and array indexing. Considerable care is therefore needed.
Specific information on use of CLAPACK is available in the Netlib archives, and general information on using C/C++ and Fortran together is available here.
All build logs are preserved in
Mac Blas Library Locations
There are regrettably a few unavoidable exceptions to the above simple recipe that are necessary if the compiler is not f77, or if the memory model is not the default, or if there is more than one version of the libraries:
- Compaq/DEC Alpha GNU/Linux:
Reason: two incompatible Fortran compilers:
The nonsuffixed and f77-suffixed libraries are hard links to the same files. It is easiest for users to make the library suffix match the compiler name.
- GNU/Linux on Intel x86:
Reason: two different LAPACK and BLAS libraries:
- SGI IRIX 6.5
Reason: three different memory models: -o32, -n32 (default), and -64:
- Sun Solaris 2.x:
Reason: f77 .o files are incompatible with those from f90 and f95:
The f90 and f95 libraries are hard links to the same files, so they can be used interchangeably. Similarly, the nonsuffixed and f77-suffixed libraries are hard links to the same files. It is easiest for users to make the library suffix match the compiler name.
Mac Blas Library Florida
Caveat: The LAPACK code on all systems has been compiled with -O optimization, and the LAPACK test suites have not yet been run.
Vendor-provided libraries are likely to have been compiled with high optimization levels, and in some cases, may be replaced by assembly-coded routines with even higher performance. They are also likely to have received extensive testing.
Linking with NAG libraries
Using the NAG libraries is documented separately.Linking with vendor-provided libraries
Most commercial UNIX vendors now provide optimized versions of the LAPACK (and often also LINPACK and EISPACK) libraries, but alas, the library names and locations are vendor dependent.
We also have the commercial NAG libraries installed on all local architectures for which they are available. Those libraries include all of EISPACK, LINPACK, LAPACK, and the BLAS.
On some systems, it is even more complex, because the libraries have been built for Fortran 77 use in one version, and for Fortran 90 in a later version.
Complexity is increased yet again when C code is linked against these libraries, because
Shared library injector mac. Right now it only supports what SMBIOS AGPM supports natively but if there are use cases out there that the SMBIOS isn't listed in the app, I could use that feedback to update the app. Most the time the AGPM settings are wrong though because most GPUs in real Macs are mobile GPUs. This AGPM kext injector generator app will generate a AGPM injector kext with the correct settings for discrete GPUs.
- the C <-> Fortran interface is not standardized with respect to external names or data types (e.g., Fortran function foo is C function foo_ on most UNIX systems, except IBM AIX and HP HP-UX, where the name remains unchanged, and on now-deceased Stardent, where it was C function FOO).
- C compilers do not know what Fortran libraries are needed, or where to find them.
- There are no standard C header files that define suitable prototypes for the Fortran libraries (although /usr/local/include/clapack.h has been installed to help out).
The various GNU/Linux distributions for Apple/IBM PowerPC, Compaq/DEC Alpha, Intel x86, and Sun SPARC do not come with LAPACK support.
In a Makefile for C and Fortran code, you might have something like this:
Shared vendor libraries are a nuisance if gcc, g++, or g77 are used, because those compilers do not know about the location of some vendor-provided libraries, and except on IBM AIX, most UNIX linkers regrettably do not by default record the location of libraries used at link time. This means that even if linking succeeds, your program may fail to run because the run-time loader cannot find the necessary libraries.
One solution is to define the environment variable LD_LIBRARY_PATH (or LPATH on Hewlett-Packad HP-UX) to a colon-separated list of shared-library directory paths. This is hardly satisfactory, since each user who runs that executable must do the same, and, on SGI IRIX 6.x systems, there are three variants of that variable, depending on the memory model chosen.
A better solution to this problem is to supply additional flags that instruct the linker to record the shared-library paths in the executable program. Unfortunately, these flags are highly compiler dependent (and not needed at all on IBM AIX):
Only one directory can be specified with each option, so you might need to do something like this:
On some UNIX systems, you can use the ldd command to check whether your executable has recorded the location of all needed libraries (taking care to undefine LD_LIBRARY_PATH for the duration of the command):
On others, you'll merely be told at run time that a certain library cannot be found, sigh..
Related libraries: LINPACK and EISPACK
Here is some old related mail:
Date: Thu, 12 Apr 2001 08:58:11 -0600 (MDT)
From: 'Nelson H. F. Beebe' <beebe@math.utah.edu>
To: Peter Alfeld <alfeld@math.utah.edu>
Subject: Re: linpack
>> do we have a double precision version of LINPACK?
Yes: unlike EISPACK, which used the same names for single and double precision, preventing using both flavors in one program, LINPACK and LAPACK both use a naming convention that identifies the precision:
>From the emacsinfo path Local -> Linpack -> NAMING-CONVENTIONS:
Thus, if you had the source code for sgeco.f, the double-precision version would be dgeco.f.
LINPACK sources are in /usr/local/math/linpack/, and each system has -llinpack available for linking.
I haven't done that for LAPACK, but most vendors have tuned LAPACK implementations available:
We don't have such a standard library on GNU/Linux systems, but the Portland Group compilers (pgcc, pgCC, pghpf, pgf77, and pgf90) provide -llapack on wasatch.math.utah.edu, a 600MHz dual-CPU Intel x86 Pentium III system. Also, on all systems, we have -lnag, which includes LAPACK. In most cases, we can expect that the vendor implementations of LAPACK include highly-tuned BLAS levels 1, 2, and 3, to produce better performance than a straightforward Fortran LAPACK compilation could produce. IBM's ESSL is a shining example of this: you might enjoy reading this new article which is available in PDF form at the URL cited.
You should also look at http://www.math.utah.edu/software
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Prerequisites
In addition to the Android NDK, you will need both Perl and a C compiler on the build host as these are currentlyrequired by the OpenBLAS build environment. Mac developer library.
Building OpenBLAS without Fortran
see below for building with clang as required by recent ndks
The prebuilt Android NDK toolchains do not include Fortran, hence parts like LAPACK cannot be built. You can still build OpenBLAS without it. For instructions on how to build OpenBLAS with Fortran, see the next section.
To use easily the prebuilt toolchains, follow building a standalone toolchain for your desired architecture.This would be arm-linux-androideabi-gcc-4.9 for ARMV7 and aarch64-linux-android-gcc-4.9 for ARMV8.
You can build OpenBLAS (0.2.19 and earlier) with:
Mac Blas Library Hours
Since we are cross-compiling, we make the libs recipe, not all. Otherwise you will get errors when trying to link/run tests as versions up to and including 0.2.19 cannot build a shared library for Android.
From 0.2.20 on, you can MUST leave off the 'libs' to get a full build, and you may want to use the softfp ABI instead of the deprecated hardfp one on ARMV7 so you would use
If you get an error about stdio.h not being found, you need to specify your sysroot in the CFLAGS argument to make likeCFLAGS=--sysroot=$NDK/platforms/android-16/arch-armWhen you are done, install OpenBLAS into the desired directory. Be sure to also use all command line optionshere that you specified for building, otherwise errors may occur as it tries to install things you did not build:
Building OpenBLAS with Fortran
Instructions on how to build the GNU toolchains with Fortran can be found here. The Releases section provides prebuilt versions, use the standalone one.
You can build OpenBLAS with:
As mentioned above you can leave off the libs argument here when building 0.2.20 and later, and you may want to add ARM_SOFTFP_ABI=1 when building for ARMV7.
Linking OpenBLAS (0.2.19 and earlier) for ARMV7
If you are using ndk-build, you need to set the ABI to hard floating points in your Application.mk:
This will set the appropriate flags for you. If you are not using ndk-build, you will want to add the following flags:
From 0.2.20 on, it is also possible to build for the softfp ABI by specifying ARM_SOFTFP_ABI=1 during the build.In that case, also make sure that all your dependencies are compiled with -mfloat-abi=softfp as well, as mixing'hard' and 'soft' floating point ABIs in a program will make it crash.
Most recent Android NDKs stopped supporting gcc, so you would need to use clang to compile OpenBLAS. clang is supported from OpenBLAS 0.2.20 version onwards. See below sections on how to build with clang for ARMV7 and ARMV8 targets.Note that you still need to build a standalone toolchain first, following building a standalone toolchain for your desired architecture.If you want to use static linking, you need to choose an API level below 23 currently due to NDK bug 272(https://github.com/android-ndk/ndk/issues/272 , the libc.a lacks a definition of stderr) that will probablybe fixed in r17 of the NDK.
Build ARMV7 with clang
On a Mac, it may also be necessary to give the complete path to the ar utility in the make command above, like so:
otherwise you may get a linker error complaining about a 'malformed archive header name at 8' when the native OSX ar command was invoked instead.
Build ARMV8 with clang
Mac Blas Library Location
Note: Using TARGET=CORTEXA57 in place of ARMV8 will pick up better optimized routines. Implementations for CORTEXA57 target is compatible with all other armv8 targets.