High-Performance Computing (HPC) often relies on optimized linear algebra libraries like LAPACK and BLAS for significant speedups in scientific and engineering applications. But for beginners, finding and using these libraries can be a hurdle. This guide helps you navigate the process of locating and utilizing LAPACK and BLAS in your HPC environment. We'll cover various scenarios and address common questions.
What are LAPACK and BLAS?
Before we dive into locating these libraries, let's briefly understand their roles. BLAS (Basic Linear Algebra Subprograms) provides fundamental routines for vector and matrix operations, such as addition, multiplication, and dot products. LAPACK (Linear Algebra PACKage) builds upon BLAS, providing higher-level routines for solving linear equations, eigenvalue problems, and singular value decompositions. These are essential building blocks for many scientific computing tasks.
Where are LAPACK and BLAS located on my system?
This depends heavily on your operating system and HPC environment. There isn't a single universal location.
Common Locations and How to Find Them:
-
Using the
locatecommand (Linux/macOS): If you're on a Linux or macOS system, thelocatecommand can be your friend. Open your terminal and type:locate libblas.soorlocate liblapack.so. This will list all files matching that pattern on your system. Note that the exact filename might vary (e.g.,libblas.a,liblapacke.so). -
Checking standard library paths: Many systems install libraries in standard locations. Check directories like
/usr/lib,/usr/local/lib,/opt/local/lib, and their subdirectories. -
Package managers: If you installed your HPC software using a package manager (like apt, yum, pacman, or brew), check the package manager's database to see where the library files are installed. For example, on Debian/Ubuntu systems you could use
apt-cache show blasto see details about the installed BLAS package, including its location. -
Environment variables: Your HPC environment might set environment variables pointing to the libraries. Check variables like
LD_LIBRARY_PATH,LIBRARY_PATH, orCPATH. Typingecho $LD_LIBRARY_PATHin your terminal (or the equivalent for other variables) will show their values. -
HPC Software Distributions: If you're using a specific HPC software distribution (like Intel Parallel Studio, or others), consult its documentation for the location of LAPACK and BLAS. These often have their own optimized versions.
What if I can't find them?
If the standard methods fail, consider these possibilities:
-
The libraries aren't installed: You might need to install them using your system's package manager. The package names vary depending on the system (e.g.,
libblas-dev,liblapacke-devon Debian/Ubuntu). -
Incorrect environment setup: Double-check that your environment variables are correctly set to include the paths containing the LAPACK and BLAS libraries.
-
Using a different name: The library files might have slightly different names on your system (e.g., variations on
libblas,liblapack). Try different variations when searching.
How do I link my code with LAPACK and BLAS?
Once you’ve located the libraries, you need to link them to your code during compilation. This typically involves using compiler flags:
- For example (using GCC):
gcc myprogram.c -llapack -lblas -lm -o myprogram
Here:
-llapacklinks the LAPACK library.-lblaslinks the BLAS library.-lmlinks the math library (often required).myprogram.cis your source code file.-o myprogramspecifies the output executable name.
The exact flags might vary slightly depending on your compiler and operating system. Consult your compiler's documentation for details.
What are some common BLAS and LAPACK alternatives?
While LAPACK and BLAS are widely used, several alternatives exist, offering specialized optimizations or features. Some examples include:
- OpenBLAS: A high-performance open-source implementation of BLAS.
- MKL (Intel Math Kernel Library): Intel's proprietary highly optimized library.
- ACML (AMD Core Math Library): AMD's counterpart to MKL.
Choosing an alternative depends on your specific needs and hardware.
This guide provides a starting point for locating and using LAPACK and BLAS in your HPC work. Remember to always refer to the documentation of your specific system and compiler for the most accurate and up-to-date information.
