Embedded Java with GCJ
This article discusses how to use GCJ, part of the GCC compiler suite, in an embedded Linux project. Like all tools, GCJ has benefits, namely the ability to code in a high-level language like Java, and its share of drawbacks as well. The notion of getting GCJ running on an embedded target may be daunting at first, but you'll see that doing so requires less effort than you may think.
After reading the article, you should be inspired to try this out on a target to see whether GCJ can fit into your next project. The Java language has all sorts of nifty features, like automatic garbage collection, an extensive, robust run-time library and expressive object-oriented constructs that help you quickly develop reliable code.
The native code compiler for Java does what is says: compiles your Java source down to the machine code for the target. This means you won't have to get a JVM (Java Virtual Machine) on your target. When you run the program's code, it won't start a VM, it will simply load and run like any other program. This doesn't necessarily mean your code will run faster. Sometimes you get better performance numbers for byte code running on a hot-spot VM versus GCJ-compiled code.
One advantage of using GCJ is that you save space by not needing the JVM. You may save money in royalties as well. Furthermore, using GCJ lets you deliver a solution using all open-source software, and that's usually a good thing.
The first thing embedded engineers reach for when creating a root filesystem for a target is trusty uClibc, a compact implementation of the glibc library. For those new to using Linux on an embedded target, the standard C library can be a bit on the large side when working with targets that may have only 8MB (for example) for a root filesystem. To conserve space on an embedded system's root filesystem, engineers will switch from the standard C library to something smaller, like uClibc. GCJ requires unicode support, which is not supported by uClibc, so glibc is a requirement.
The standard library for GCJ weighs in at 16MB, so even if you could conserve space by switching to a smaller standard C library, it wouldn't make that much difference overall. The standard GCJ library can be trimmed by removing support for executing Java byte code, but the loss of that feature would reduce the overall value of GCJ.
Because this article is about using GCJ in an embedded environment, it shows you how to build a cross compiler and a simple root filesystem for the target system. For those new to embedded development, a cross compiler builds code that runs on a processor different from the machine where the compilation occurred. The machine that runs the compiler is called the host and the one where the code runs is called the target.
In this article, the target system is a PPC 745/755-based system running at 350MHz. This particular board comes wrapped in a translucent case with a monitor and hard drive and is otherwise known as an iMac. Okay, this is hardly a prime example of an embedded system, but it does present some of the same challenges you'll encounter with a true embedded system. The things you learn here should apply well to embedded systems using other processors.
The host system is a run-of-the-mill IBM ThinkPad notebook running a Pentium III processor. Yellow Dog Linux is already running on the host system, but with a little sleight of hand, we'll make it use the root filesystem created in the article for testing.
First, we need a cross compiler that runs on our Pentium machine that creates code for a PowerPC 750-based processor. Building a cross compiler for a target system can be a very tedious process; a working compiler is more than GCC, it also contains some extra tools (affectionately named binutils) and the standard libraries for the language.
To get a cross compiler up and running quickly, try using the crosstool package, compliments of Dan Kegel. Crosstool does all of the hard work necessary to get a cross compiler built: it fetches the source and patches, applies the patches, configures the packages and kicks off the build. After obtaining and unpacking crosstool, here are the steps for building your GCJ cross compiler:
$ export TARBALLS_DIR=~/crosstool-download $ export RESULT_TOP=/opt/crosstool $ export GCC_LANGUAGES="c,c++,Java" $ eval `cat powerpc-750.dat gcc-4.0.1-glibc-2.2.2.dat' sh.all --notest
While waiting for the compilation to finish, let's take a look at what we just did to start our crosstool build. TARBALLS_DIR is the location where crosstool downloads its files. Crosstool fetches all of the files it needs for a build by default. RESULT_TOP is the installation directory of the cross compiler. Lastly, GCC_LANGUAGES controls which language front ends will be enabled for the compiler. GCC supports many different language front ends and each front end adds a considerable amount of time to the compilation process, so only the necessary ones were selected for this toolchain build.
The last line, for those lacking their bash script-foo license, dumps the two dat files on the command line and executes the all.sh script with the parameter --notest. To make building a cross compiler easy, crosstool includes configuration files with the correct environment variables set for the target processor and the gcc/glibc combination. In this case, crosstool builds a gcc 4.0.1 with glibc 2.2.2 targeting a PPC 750 processor. Crosstool includes scripts for all major processor architectures and glib/gcc combinations.
When the build finishes, the cross compiler will be installed at $RESULT_TOP/gcc-4.0.1-glibc-2.2.2/powerpc-750-linux-gnu/bin. Add this to your path to make invoking the cross compiler easier.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
Join Linux Journal's Mike Diehl and Pat Cameron of Help Systems.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide