make plays a critical role in the development process. It combines the elements of a project to create an application while allowing the developer to avoid the subtle errors caused by accidentally omitting steps of the build. However, if developers avoid using
make, because they feel the makefile is too slow, all the benefits of
make are lost. It is important, therefore, to ensure that the makefile be crafted to be as efficient as possible.
Performance issues are always tricky, but become even more so when the perception of users and different paths through the code are considered. Not every target of a makefile is worth optimizing. Even radical optimizations might not be worth the effort depending on your environment. For instance, reducing the time of an operation from 90 minutes to 45 minutes may be immaterial since even the faster time is a “go get lunch” operation. On the other hand, reducing a task from 2 minutes to 1 might be received with cheers if developers are twiddling their thumbs during that time.
When writing a makefile for efficient execution, it is important to know the costs of various operations and to know what operations are being performed. In the following sections, we will perform some simple benchmarking to quantify these general comments and present techniques to help identify bottlenecks.
A complementary approach to improving performance is to take advantage of parallelism and local network topology. By running more than one command script at a time (even on a uniprocessor), build times can be reduced.
Here we measure the performance of some basic operations in
make. Table 10-1 shows the results of these measurements. We’ll explain each test and suggest how they might affect makefiles you write.
Seconds per execution (Windows)
Executions per second (Windows)
Seconds per execution (Linux)
Executions per second (Linux)
The Windows tests were run on a 1.9-GHz Pentium 4 (approximately 3578 Bogo-Mips) with 512 MB RAM running Windows XP. The Cygwin version of
make 3.80 was used, started from an
rxvt window. The Linux tests were run on a 450-MHz Pentium 2 (891 BogoMips) with 256 MB of RAM running Linux RedHat 9.
The subshell used by
make can have a significant effect on the overall performance of the makefile. The
bash shell is a complex, fully featured shell, and therefore large. The
ash shell is a much smaller, with fewer features but adequate for most tasks. To complicate matters, if
bash is invoked from the filename /bin/sh, it alters its behavior significantly to conform more closely to the standard shell. On most Linux systems the file /bin/sh is a symbolic link to
bash, while in Cygwin /bin/sh is really ash. To account for these differences, some of the tests were run three times, each time using a different shell. The shell used is indicated in parentheses. When “(sh)” appears, it means that
bash was linked to the file named /bin/sh.
The first three tests, labeled make, give an indication of how expensive it is to run
make if there is nothing to do. The makefile contains:
SHELL := /bin/bash .PHONY: x x: $(MAKE) --no-print-directory --silent --question make-bash.mk; \ ...this command repeated 99 more times...
The word “bash” is replaced with the appropriate shell name as required.
We use the
--silent commands to eliminate unnecessary computation that might skew the timing test and to avoid cluttering the timing output values with irrelevant text. The
--question option tells
make to simply check the dependencies without executing any commands and return an exit status of zero if the files are up to date. This allows
make to do as little work as possible. No commands will be executed by this makefile and dependencies exist for only one
.PHONY target. The command script executes
make 100 times. This makefile, called make-bash.mk, is executed 10 times by a parent makefile with this code:
define ten-times TESTS += $1 .PHONY: $1 $1: @echo $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2; \ time $(MAKE) --no-print-directory --silent $2 endef .PHONY: all all: $(eval $(call ten-times, make-bash, -f make-bash.mk)) all: $(TESTS)
The time for these 1,000 executions is then averaged.
As you can see from the table, the Cygwin
make ran at roughly 22 executions per second or 0.044 seconds per run, while the Linux version (even on a drastically slower CPU) performed roughly 61 executions per second or 0.016 seconds per run. To verify these results, the native Windows version of
make was also tested and did not yield any dramatic speed up. Conclusion: while process creation in Cygwin
make is slightly slower than a native Windows
make, both are dramatically slower than Linux. It also suggests that use of recursive
make on a Windows platform may perform significantly slower than the same build run on Linux.
As you would expect, the shell used in this test had no effect on execution time. Because the command script contained no shell special characters, the shell was not invoked at all. Rather,
make executed the commands directly. This can be verified by setting the
SHELL variable to a completely bogus value and noting that the test still runs correctly. The difference in performance between the three shells must be attributed to normal system variance.
# 10000 assignments z := 10 ...repeated 10000 times... .PHONY: x x: ;
This makefile is then run using our
ten-times function in the parent makefile.
The assignment is obviously very fast. Cygwin
make will execute 8130 assignments per second while the Linux system can do 10,989. I believe the performance of Windows for most of these operations is actually better than the benchmark indicates because the cost of creating the
make process 10 times cannot be reliably factored out of the time. Conclusion: because it is unlikely that the average makefile would perform 10,000 assignments, the cost of variable assignment in an average makefile is negligible.
The next two benchmarks measure the cost of a
subst function call. The first uses a short 10-character string with three substitutions:
# 10000 subst on a 10 char string dir := ab/cd/ef/g x := $(subst /, ,$(dir)) ...repeated 10000 times... .PHONY: x x: ;
This operation takes roughly twice as long as a simple assignment, or 3891 operations per second on Windows. Again, the Linux system appears to outperform the Windows system by a wide margin. (Remember, the Linux system is running at less than one quarter the clock speed of the Windows system.)
The longer substitution operates on a 1000-character string with roughly 100 substitutions:
# Ten character file dir := ab/cd/ef/g # 1000 character path p100 := $(dir);$(dir);$(dir);$(dir);$(dir);... p1000 := $(p100)$(p100)$(p100)$(p100)$(p100)... # 10000 subst on a 1000 char string x := $(subst ;, ,$(p1000)) ...repeated 10000 times... .PHONY: x x: ;
The next three benchmarks measure the speed of the same substitution using
sed. The benchmark contains:
# 100 sed using bash SHELL := /bin/bash .PHONY: sed-bash sed-bash: echo '$(p1000)' | sed 's/;/ /g' > /dev/null ...repeated 100 times...
When we factor in the cost of the shell, we see that
ash on Windows does provide a useful speed-up. With
sed is only 39 times slower than subst! (wink) On Linux, the shell used has a much more profound effect. Using
sed is only five times slower than
subst. Here we also notice the curious effect of renaming
sh. On Cygwin, there is no difference between a
/bin/bash and one named
/bin/sh, but on Linux, a
bash linked to
/bin/sh performs significantly better.
The final benchmark simply invokes the
make shell command to evaluate the cost of running a subshell. The makefile contains:
# 100 $(shell ) using bash SHELL := /bin/bash x := $(shell :) ...repeated 100 times... .PHONY: x x: ;
There are no surprises here. The Windows system is slower than Linux, with
ash having an edge over
bash. The performance gain of
ash is more pronounced—about 50
% faster. The Linux system performs best with
ash and slowest with
bash (when named “bash”).
Benchmarking is a never-ending task, however, the measurements we’ve made can provide some useful insight. Create as many variables as you like if they help clarify the structure of the makefile because they are essentially free. Built-in
make functions are preferred over running commands even if you are required by the structure of your code to reexecute the
make function repeatedly. Avoid recursive
make or unnecessary process creation on Windows. While on Linux, use
ash if you are creating many processes.
Finally, remember that in most makefiles, the time a makefile takes to run is due almost entirely to the cost of the programs run, not
make or the structure of the makefile. Usually, reducing the number of programs run will be most helpful in reducing the execution time of a makefile.
Unnecessary delays in makefiles come from several sources: poor structuring of the makefile, poor dependency analysis, and poor use of
make functions and variables. These problems can be masked by
make functions such as
shell that invoke commands without echoing them, making it difficult to find the source of the delay.
Dependency analysis is a two-edged sword. On the one hand, if complete dependency analysis is performed, the analysis itself may incur significant delays. Without special compiler support, such as supplied by
jikes, creating a dependency file requires running another program, nearly doubling compilation time. The advantage of complete dependency analysis is that it allows
make to perform fewer compiles. Unfortunately, developers may not believe this benefit is realized and write makefiles with less complete dependency information. This compromise almost always leads to an increase in development problems, leading other developers to overcompensate by compiling more code than would be required with the original, complete dependency information.
To formulate a dependency analysis strategy, begin by understanding the dependencies inherent in the project. Once complete dependency information is understood, you can choose how much to represent in the makefile (computed or hardcoded) and what shortcuts can be taken during the build. Although none of this is exactly simple, it is straightforward.
Once you’ve determined your makefile structure and necessary dependencies, implementing an efficient makefile is usually a matter of avoiding some simple pitfalls.
One of the most common performance-related problems is using recursive variables instead of simple variables. For example, because the following code uses the
= operator instead of
:=, it will execute the
date command every time the
DATE variable is used:
DATE = $(shell date +%F)
+%F option instructs
date to return the date in “yyyy-mm-dd” format, so for most users the repeated execution of
date would never be noticed. Of course, developers working around midnight might get a surprise!
make doesn’t echo commands executed from the
shell function, it can be difficult to determine what is actually being run. By resetting the
SHELL variable to
/bin/sh -x, you can trick
make into revealing all the commands it executes.
DATE = $(shell date +%F) OUTPUT_DIR = out-$(DATE) make-directories := $(shell [ -d $(OUTPUT_DIR) ] || mkdir -p $(OUTPUT_DIR)) all: ;
When run with a debugging shell, we can see:
$ make SHELL='/bin/sh -x' + date +%F + date +%F + '[' -d out-2004-03-30 ']' + mkdir -p out-2004-03-30 make: all is up to date.
This clearly shows us that the
date command was executed twice. If you need to perform this kind of shell trace often, you can make it easier to access with:
ifdef DEBUG_SHELL SHELL = /bin/sh -x endif
Another way commands are hidden is through the use of the silent command modifier,
@. It can be useful at times to be able to disable this feature. You can make this easy by defining a variable,
QUIET, to hold the @ sign and use the variable in commands:
ifndef VERBOSE QUIET := @ endif ... target: $(QUIET) echo Building target...
When it becomes necessary to see commands hidden by the silent modifier, simply define
VERBOSE on the command line:
$ make VERBOSE=1 echo Building target... Building target...
When simple variables are used in conjunction with the
make evaluates all the
shell function calls as it reads the makefile. If there are many of these, or if they perform expensive computations,
make can feel sluggish. The responsiveness of
make can be measured by timing
make when invoked with a nonexistent target:
$ time make no-such-target make: *** No rule to make target no-such-target. Stop. real 0m0.058s user 0m0.062s sys 0m0.015s
This code times the overhead that
make will add to any command executed, even trivial or erroneous commands.
Because recursive variables reevaluate their righthand side every time they are expanded, there is a tendency to express complex calculations as simple variables. However, this decreases the responsiveness of
make for all targets. It seems that there is a need for another kind of variable, one whose righthand side is evaluated only once the first time the variable is evaluated, but not before.
# $(call find-compilation-dirs, root-directory) find-compilation-dirs = \ $(patsubst %/,%, \ $(sort \ $(dir \ $(shell $(FIND) $1 -name '*.java')))) PACKAGE_DIRS := $(call find-compilation-dirs, $(SOURCE_DIR))
Ideally, we would like to perform this
find operation only once per execution, but only when the
PACKAGE_DIRS variable is actually used. This might be called lazy initialization. We can build such a variable using
eval like this:
PACKAGE_DIRS = $(redefine-package-dirs) $(PACKAGE_DIRS) redefine-package-dirs = \ $(eval PACKAGE_DIRS := $(call find-compilation-dirs, $(SOURCE_DIR)))
The basic approach is to define
PACKAGE_DIRS first as a recursive variable. When expanded, the variable evaluates the expensive function, here
find-compilation-dirs, and redefines itself as a simple variable. Finally, the (now simple) variable value is returned from the original recursive variable definition.
Let’s go over this in detail:
make reads these variables, it simply records their righthand side because the variables are recursive.
The first time the
PACKAGE_DIRS variable is used,
make retrieves the righthand side and expands the first variable,
The value of
redefine-package-dirs is a single function call,
The body of the
eval redefines the recursive variable,
PACKAGE_DIRS, as a simple variable whose value is the set of directories returned by
PACKAGE_DIRS has been initialized with the directory list.
make continues to expand the original righthand side of
PACKAGE_DIRS. The only thing left to do is expand the variable
make looks up the value of the variable, sees a simple variable, and returns its value.
The only really tricky part of this code is relying on
make to evaluate the righthand side of a recursive variable from left to right. If, for instance,
make decided to evaluate
$(redefine-package-dirs), the code would fail.
The procedure I just described can be refactored into a function,
# $(call lazy-init,variable-name,value) define lazy-init $1 = $$(redefine-$1) $$($1) redefine-$1 = $$(eval $1 := $2) endef # PACKAGE_DIRS - a lazy list of directories $(eval \ $(call lazy-init,PACKAGE_DIRS, \ $$(call find-compilation-dirs,$(SOURCE_DIRS))))
Another way to improve the performance of a build is to take advantage of the parallelism inherent in the problem the makefile is solving. Most makefiles perform many tasks that are easily carried out in parallel, such as compiling C source to object files or creating libraries out of object files. Furthermore, the very structure of a well-written makefile provides all the information necessary to automatically control the concurrent processes.
Example 10-1 shows our
mp3_player program executed with the jobs option,
-j 2). Figure 10-1 shows the same
make run in a pseudo UML sequence diagram. Using
make to update two targets in parallel when that is possible. When
make updates targets in parallel, it echos commands in the order in which they are executed, interleaving them in the output. This can make reading the output from parallel
make more difficult. Let’s look at this output more carefully.
$ make -f ../ch07-separate-binaries/makefile --jobs=2 1 bison -y --defines ../ch07-separate-binaries/lib/db/playlist.y 2 flex -t ../ch07-separate-binaries/lib/db/scanner.l > lib/db/scanner.c 3 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -M ../ch07-separate-binaries/app/player/play_mp3.c | \ sed 's,\(play_mp3\.o\) *:,app/player/\1 app/player/play_mp3.d: ,' > app/player/play_ mp3.d.tmp 4 mv -f y.tab.c lib/db/playlist.c 5 mv -f y.tab.h lib/db/playlist.h 6 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -M ../ch07-separate-binaries/lib/codec/codec.c | \ sed 's,\(codec\.o\) *:,lib/codec/\1 lib/codec/codec.d: ,' > lib/codec/codec.d.tmp 7 mv -f app/player/play_mp3.d.tmp app/player/play_mp3.d 8 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -M lib/db/playlist.c | \ sed 's,\(playlist\.o\) *:,lib/db/\1 lib/db/playlist.d: ,' > lib/db/playlist.d.tmp 9 mv -f lib/codec/codec.d.tmp lib/codec/codec.d 10 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -M ../ch07-separate-binaries/lib/ui/ui.c | \ sed 's,\(ui\.o\) *:,lib/ui/\1 lib/ui/ui.d: ,' > lib/ui/ui.d.tmp 11 mv -f lib/db/playlist.d.tmp lib/db/playlist.d 12 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -M lib/db/scanner.c | \ sed 's,\(scanner\.o\) *:,lib/db/\1 lib/db/scanner.d: ,' > lib/db/scanner.d.tmp 13 mv -f lib/ui/ui.d.tmp lib/ui/ui.d 14 mv -f lib/db/scanner.d.tmp lib/db/scanner.d 15 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -c -o app/player/play_mp3.o ../ch07-separate-binaries/app/player/play_mp3.c 16 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -c -o lib/codec/codec.o ../ch07-separate-binaries/lib/codec/codec.c 17 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -c -o lib/db/playlist.o lib/db/playlist.c 18 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -c -o lib/db/scanner.o lib/db/scanner.c ../ch07-separate-binaries/lib/db/scanner.l: In function yylex: ../ch07-separate-binaries/lib/db/scanner.l:9: warning: return makes integer from pointer without a cast 19 gcc -I lib -I ../ch07-separate-binaries/lib -I ../ch07-separate-binaries/include -c -o lib/ui/ui.o ../ch07-separate-binaries/lib/ui/ui.c 20 ar rv lib/codec/libcodec.a lib/codec/codec.o ar: creating lib/codec/libcodec.a a - lib/codec/codec.o 21 ar rv lib/db/libdb.a lib/db/playlist.o lib/db/scanner.o ar: creating lib/db/libdb.a a - lib/db/playlist.o a - lib/db/scanner.o 22 ar rv lib/ui/libui.a lib/ui/ui.o ar: creating lib/ui/libui.a a - lib/ui/ui.o 23 gcc app/player/play_mp3.o lib/codec/libcodec.a lib/db/libdb.a lib/ui/libui.a -o app/player/play_mp3
make must build the generated source and dependency files. The two generated source files are the output of
lex. This accounts for commands 1 and 2. The third command generates the dependency file for play_mp3.c and is clearly begun before the dependency files for either playlist.c or scanner.c are completed (by commands 4, 5, 8, 9, 12, and 14). Therefore, this
make is running three jobs in parallel, even though the command-line option requests two jobs.
mv commands, 4 and 5, complete the playlist.c source code generation started with command 1. Command 6 begins another dependency file. Each command script is always executed by a single
make, but each target and prerequisite forms a separate job. Therefore, command 7, which is the second command of the dependency generation script, is being executed by the same
make process as command 3. While command 6 is probably being executed by a
make spawned immediately following the completion of the
make that executed commands 1-4-5 (processing the
yacc grammar), but before the generation of the dependency file in command 8.
The dependency generation continues in this fashion until command 14. All dependency files must be complete before
make can move on to the next phase of processing, re-reading the makefile. This forms a natural synchronization point that
make automatically obeys.
Once the makefile is reread with the dependency information,
make can continue the build process in parallel again. This time
make chooses to compile all the object files before building each of the archive libraries. This order is nondeterministic. That is, if the makefile is run again, it may be that the libcodec.a library might be built before the playlist.c is compiled, since that library doesn’t require any objects other than codec.o. Thus, the example represents one possible execution order amongst many.
Finally, the program is linked. For this makefile, the link phase is also a natural synchronization point and will always occur last. If, however, the goal was not a single program but many programs or libraries, the last command executed might also vary.
Running multiple jobs on a multiprocessor obviously makes sense, but running more than one job on a uniprocessor can also be very useful. This is because of the latency of disk I/O and the large amount of cache on most systems. For instance, if a process, such as
gcc, is idle waiting for disk I/O it may be that data for another task such as
ar is currently in memory. In this case, it would be good to allow the task with available data to proceed. In general, running
make with two jobs on a uniprocessor is almost always faster than running one job, and it is not uncommon for three or even four tasks to be faster than two.
--jobs option can be used without a number. If so,
make will spawn as many jobs as there are targets to be updated. This is usually a bad idea, because a large number of jobs will usually swamp a processor and can run much slower than even a single job.
Another way to manage multiple jobs is to use the system load average as a guide. The load average is the number of runnable processes averaged over some period of time, typically 1 minute, 5 minutes, and 15 minutes. The load average is expressed as a floating point number. The
-l) option gives
make a threshold above which new jobs cannot be spawned. For example, the command:
$ make --load-average=3.5
make to spawn new jobs only when the load average is less than or equal to 3.5. If the load average is greater,
make waits until the average drops below this number, or until all the other jobs finish.
When writing a makefile for parallel execution, attention to proper prerequisites is even more important. As mentioned previously, when
--jobs is 1, a list of prerequisites will usually be evaluated from left to right. When
--jobs is greater than 1, these prerequisites may be evaluated in parallel. Therefore, any dependency relationship that was implicitly handled by the default left to right evaluation order must be made explicit when run in parallel.
Another hazard of parallel
make is the problem of shared intermediate files. For example, if a directory contains both foo.y and bar.y, running
yacc twice in parallel could result in one of them getting the other’s instance of y.tab.c or y.tab.h or both moved into its own .c or .h file. You face a similar hazard with any procedure that stores temporary information in a scratch file that has a fixed name.
Another common idiom that hinders parallel execution is invoking a recursive
make from a shell
dir: for d in $(SUBDIRS); \ do \ $(MAKE) --directory=$$d; \ done
As mentioned in the section Recursive make in Chapter 6,
make cannot execute these recursive invocations in parallel. To achieve parallel execution, declare the directories
.PHONY and make them targets:
.PHONY: $(SUBDIRS) $(SUBDIRS): $(MAKE) --directory=$@
make supports a little known (and only slightly tested) build option for managing builds that uses multiple systems over a network. The feature relies upon the Customs library distributed with
Pmake is an alternate version of
make written in about 1989 by Adam de Boor (and maintained ever since by Andreas Stolcke) for the Sprite operating system. The Customs library helps to distribute a
make execution across many machines in parallel. As of version 3.77, GNU
make has included support for the Customs library for distributing
To enable Customs library support, you must rebuild
make from sources. The instructions for this process are in the README.customs file in the
make distribution. First, you must download and build the
pmake distribution (the URL is in the README), then build
make with the
The heart of the Customs library is the customs daemon that runs on each host participating in the distributed
make network. These hosts must all share a common view of the filesystem, such as NFS provides. One instance of the customs daemon is designated the master. The master monitors hosts in the participating hosts list and allocates jobs to each member. When
make is run with the
--jobs flag greater than 1,
make contacts the master and together they spawn jobs on available hosts in the network.
The Customs library supports a wide range of features. Hosts can be grouped by architecture and rated for performance. Arbitrary attributes can be assigned to hosts and jobs can be allocated to hosts based on combinations of attributes and boolean operators. Additionally, host status such as idle time, free disk space, free swap space, and current load average can also be accounted for when processing jobs.
If your project is implemented in C, C++, or Objective-C you should also consider
distcc (http://distcc.samba.org) for distributing compiles across several hosts.
distcc was written by Martin Pool and others to speedup Samba builds. It is a robust and complete solution for projects written in C, C++, or Objective-C. The tool is used by simply replacing the C compiler with the
$ make --jobs=8 CC=distcc
For each compilation,
distcc uses the local compiler to preprocess the output, then ships the expanded source to an available remote machine for compilation. Finally, the remote host returns the resulting object file to the master. This approach removes the necessity for having a shared filesystem, greatly simplifying installation and configuration.
The set of worker or volunteer hosts can be specified in several ways. The simplest is to list the volunteer hosts in an environment variable before starting
$ export DISTCC_HOSTS='localhost wasatch oops'
distcc is very configurable with options for handling host lists, integrating with the native compiler, managing compression, search paths, and handling failure and recovery.
ccache is another tool for improving compilation performance, written by Samba project leader Andrew Tridgell. The idea is simple, cache the results of previous compiles. Before performing a compile, check if the cache already contains the resulting object files. This does not require multiple hosts, or even a network. The author reports a 5 to 10 times speed up in common compilations. The easiest way to use
ccache is to prefix your compiler command with
$ make CC='ccache gcc'
ccache can be used together with
distcc for even greater performance improvements. In addition, both tools are available in the Cygwin tool set.
 In practice, compilation time grows linearly with the size of the input text and this time is almost always dominated by disk I/O. Similarly, the time to compute dependencies using the simple
-M option is linear and bound by disk I/O.