SeqQuest Build Guide

This page provides guidance and instructions for building an executable from the shipped code package. Often this will be as simple as unpacking the code, and then “make” or “make platform“, but should rarely be much more complicated than that. Mostly, you will be visiting this page in the uncommon event that something broke, and are looking for details and instructions on how to fix the make.

The code is very compact, is written entirely in f77, and is fully self-contained except for the need to invoke LAPACK/BLAS math libraries. Hence, the code has a relatively simple build procedure. Usually, one of the named options within the provided makefile will build a working executable, by typing “make platform” and, at worst, you may need to modify the makefile to specify the appropriate compiler, some common compiler flags, and/or the location of the math libraries. It is easier than it sounds, and the provided makefile gives lots of guidance. And this web page is intended to help you through the process.

Getting everything ready

You will need a unix or linux computer. The code can be and has been made to run on a PC or Mac, but unpacking the code package requires the use of some utilities. You will need a Fortran compiler, and you should have LAPACK/BLAS libraries installed on the target machine (not required but highly recommended for performance reasons, and because I do not regularly test the make with the explicitly compiled math source).

You should set up a new empty directory for the code, and place the shipped package in that directory and unpack.

The libraries of atom files that the code needs to operate come in a separate package, and you should place them in their own directories, segregated by functional.

Unpacking the shipped code package

Eventually I will give in and deliver the package as a tarball. However, for historical reasons (don’t ask), the code currently is delivered as a “sh”-unpackable file.

  1. Prepare an empty directory for the source package
  2. Put the shipped package in that directory
  3. then finally “sh” the file

That’s all. You will see a collection of files in the directory. The procedure does not modify any other files, it does not create subdirectories or new directories anywhere on your system, does not require setting environmental variables, or anything. Really. It’s that simple.

The files you get

Unpacking gives you a small number of files:

READ.METhe name says it all – brief instructions to make the code
makefileThe default makefile for the code
lcaomain.fThe main program for the code
lcao.paramsDimension parameters for the code
lcaosubs.fAll the functional subroutines
utl_*.fThe configuration files for the code. All the machine/system dependent code are in these routines, and the code can usually be reconfigured for the idiosyncracies of almost any environment by modifying the routines here: timing diagnostics, file systems, I/O management, parallel handling, etc. Currently only two versions:
utl_gen.f – general usage
utl_mpi.f – MPI version
Yup – machine/system dependence in the code is absolutely minimal.
lapack.f, blas.fExplicit source for the LAPACK/BLAS routines (obtained from netlib) required by the code, in the event that LAPACK/BLAS libraries are not available on a target platform.
lapackx.fExpert drivers for eigensolver routines, that are frequently not part of vendor LAPACK libraries, and hence are explicitly compiled and linked into the code.
linpack.fSome isolated LINPACK routines that the code uses (these will eventually be either purged or replaced).

Making an executable

One of two means. You can:

  1. use a named make, e.g. “make sgi”, to invoke one of the existing combinations (examine the makefile)
  2. edit the menus at the beginning of the makefile to select the compiler, its flags, and specify the location of the math libraries, and then type “make”.

Your executable, should the make be successful, will appear as “lcao.x”.

Selecting the compiler and compiler flags

You may need to tell the makefile which Fortran compiler to use, and where to find it. The code has been made to run with every Fortran compiler we have run across, but different compilers may require setting some compiler flags. Some common combinations are named in the makefile (e.g. “make sgi”), and menus of compilers and their flags are listed (commented out) in the makefile that should allow for a makefile tailored to the special case of any platform. The make does use full optimization (ruthless pruning of non-porting and non-optimizable code makes this possible).

The most common compiler names:

FC = f77, g77 (gnu), mpif77, …

Standard compiler flags:

FFLAGS = -O -fast

Alternate standard, for some compilers do not recognize “-fast”:


gnu Fortran, g77, often (not always) balks at the way memory is passed in the code. The “noglobal” flag circumvents this objection:

FFLAGS = -O -fnoglobal

SGI’s are special:

FFLAGS = -O3 -mips4 -OPT:IEEE_arithmetic=3:alias=restrict

Other machines and compilers occasionally have other requirements.

Math libraries

You may need to select/modify the location of the math libraries in the makefile.

The code makes liberal use of LAPACK and BLAS, to invoke specific functionality, e.g. eigensolvers, and to enhance performance of the code. The name and location of the math libraries will vary from system to system. On many SGI’s, the math libraries are invoked by linking in -lcomplib. On some Alpha-based machines, the libraries can be invoked with -ldxml, but on more recent Compaq-vintage Alphas this has become -lcxml. IBM and Intel machines have yet different conventions. If you have a platform that did not come equipped with a vendor-supplied math library, ATLAS-generated libraries will work well, but you will need to specify their location to link them.

Alternately, you can compile and link the math routines downloaded from NETLIB in the files (lapack.f, blas.f) sent with the package. Be aware that using these compiled (not-optimized) routines can significantly slow performance in key parts of the code. In particular, the BLAS/3 implementation of the grid integrals can be THREE times slower or worse. When linked to compiled math source rather optimized libraries, the input files should add an instruction to bypass the BLAS/3 routines (see the command options) and use the explicitly coded paths in the code.

Important note: The code requires Version 3.0 of LAPACK. Earlier versions WILL fail.

Reconfiguring the code

Only if absolutely desperate and after consultation …

The package has very little code that is truly machine dependent, but what little machine dependence there may be has been isolated in a small set of routines in the “utl_*.f” files, that handle I/O units and file structure, timing and error handling, etc., functions that can be sensitive to the specific environment. These are segregated and organized in a fashion to make it easier to configure the code to the idiosyncrasies of a given platform. Currently, only two configurations are needed: a standard general version and a version to enable MPI-NEB, reflecting the militantly generic approach to programming structures used in the code (if it breaks, it’s gone). However, some computing platforms have special needs. An some old Alpha machines, the system had limits on the length of a single written record; it would write any length record you asked, but a read would intermittently and irreproducibly fail. Some systems have special conventions for connecting to the file system (esp. parallel file systems). If you need to alter the convention for file names, or what the default standard out/in units are. If your platform uses non-standard timing routines. All these potentially machine-dependent aspects can be addressed in the utl_*.f file. The code handles many system-dependent needs through pseudo-modules that are initialized in the STARTX routine. The utl_* routines should only be modified as a last resort and only after acquiring a detailed understanding of the problem. Handling machine dependencies without introducing other problems is an awkward enterprise.

Redimensioning the code – easy

Sometimes you want to run a calculation that is larger than what the code dimension parameters allow (these are echo’d in the output). The code output will usually tell you exactly what it needs to run. It is a simple procedure to modify the code size: edit “lcao.params”, the dimension file for the code, and recompile the main routine and relink the code.

The parameters in “lcao.params” define the limits on the code. This file is used in only one place: it is inserted via an “include” into the main program “lcaomain.f”. The virtue of this single use is that a redimensioned executable can be built by simply recompiling the main program (quick) and not the entire code (slower). The bulk of the code is in the subroutines file “lcaosubs.f”, and those subroutines are completely insensitive to dimensions.

There are two kinds of parameters in the “lcao.params” file: those that determine specific problem aspects, and those that fix available memory.

Most of the parameters place limits on discrete problem aspects: number of atams, number of basis functions, k-points, symmetries, etc. It is clear what they refer to, and they can usually be modified rather freely as they do not allocate large amounts of memory. If your calculation requests a larger problem in some respect than what the code is dimensioned for, the input routines will stop and point out what parameter needs to be modified. Modify that parameter in “lcao.params” and recompile.

The parameter “maxwkd” specifies the size of the principal workspace used in the code, and determines the amount of memory the code can use. At initialization, the code creates one huge real*8 workspace dimensioned to “maxwkd”, and then dynamically allocates memory it needs from this workspace. Before entering any computationally expensive routines, the code does an exact forecast of the memory needed to complete, and will stop if it sees it has insufficient to complete and will output the minimum necessary memory to finish. Modify “maxwkd” in “lcao.params” accordingly and recompile. The biggest workspace you can have –the maximum you can set “maxwkd”– is limited by the physical memory of your platform. On a 256MB machine, the largest you can set “maxwkd” is about 30M, on 512MB about 60M, and on 1GB about 110M. The exact limit will vary depending on the system, and how much space the OS reserves for other purposes.


Surprisingly, not much to say here, except to do a careful reading of the procedures above. This page is itself a troubleshooting guide that you will consult only if a trivial make failed. Detailed attention has gone toward making the code portable and robust. The rule that “if it breaks, it’s gone” has served the code well.