Welcome!

Java IoT Authors: Yeshim Deniz, Pat Romanski, Liz McMillan, Zakia Bouachraoui, Carmen Gonzalez

Related Topics: Java IoT, IBM Cloud, Weblogic

Java IoT: Article

Java vs C++ "Shootout" Revisited

Java vs C++ "Shootout" Revisited

Keith Lea writes of the benchmark, on his results page, "I was sick of hearing people say Java was slow, when I know it's pretty fast, so I took the benchmark code for C++ and Java from the now outdated Great Computer Language Shootout and ran the tests myself."

Lea used G++ (GCC) 3.3.1 20030930 (with glibc 2.3.2-98) for the C++, with the -O2 flag (for both i386 and i686). He compiled the Java code normally with the Sun Java 1.4.2_01 compiler, and ran it with the Sun 1.4.2_01 JVM. He ran the tests on Red Hat Linux 9 / Fedora Test1 with the 2.4.20-20.9 kernel on a T30 laptop. The laptop "has a Pentium 4 mobile chip, 512MB of memory, a sort of slow disk," he notes.

The results he got were that Java is significantly faster than optimized C++ in many cases.

"They also show that no one should ever run the client JVM when given the choice," Lea adds. ("Everyone has the choice," he says. To run the server VM, see instructions in the Using the Server JVM section below.)

JDJ has agreed to post online anyone else's results as long as they use Java 1.4.2 or higher and any version of GCC that produces faster or equivalent code than the 3.3.1 I used. We encourage you to download the source and/or the binaries and perform the tests yourself, with your favorite compiler and on your favorite platform.


Lea's Data and Results

JVM startup time was included in these results. "That means even with JVM startup time, Java is still faster than C++ in many of these tests," says Lea.

Some of the C++ tests would not compile. "I've never been very good at decoding GCC's error messages," he admits, "so if I couldn't fix a test with a trivial modification, I didn't include it in my benchmarks."

Lea also modified one of the tests, the string concatenation test for Java.

"The test was creating a new StringBuffer in each iteration of the loop, which was just silly," he explains. "I updated the code to use a single StringBuffer and appending to it inside the loop."

(The updated tests at the original shootout use this new method.)

"Java lost this benchmark even with the modifications," Lea declares. "So if anyone wants to accuse me of biasing the results, they're going to have to try harder."

Several versions of some of the C++ tests (like matrix) were present in the original shootout source, he continues. 

"I used the versions without numbers in them, like matrix.g++ instead of matrix.g++2. I don't know which of these were used in the original benchmarks, but from my quick experimenting, the numberless ones generally ran faster than their numbered counterparts."

"Looking at them again," Lea says, "matrix.g++3 runs faster than the matrix.g++ that I use. However, it still runs slower than the Java version, so I don't plan to modify the graph/data unless someone asks me to, since getting that graph in the first place was sort of a pain.)"

He continues: "I've been told that the C++ code for the Method Call benchmark returns by value while the Java code returns by reference, and that modifying the C++ code to pass a pointer makes that benchmark faster. However, even with the modification, the C++ version still runs slower than the Java version."

Lea ran th Java and the C++ tests to "warm up" (both the Java and C++ tests got faster after he ran them a few times).

"I've been told that these tests are invalid because they were run with GCC," he concedes, adding: "I have seen both benchmarks that show GCC producing faster code than Visual Studio's VC++ compiler, and benchmarks showing the opposite. If I update the benchmarks with another compiler added, it will be the Intel C++ Compiler, which I'm pretty sure produces faster code than VC++."

Lea says he's been accused of biasing the results by using the -O2 option for GCC, "supposedly because -O2 optimizes for space, thus slowing down the benchmark," he explains.

But this is not what -O2 does, he points out, referring to the GCC -O documentation:

JVM startup time was included in these results. "That means even with JVM startup time, Java is still faster than C++ in many of these tests," says Lea.

Some of the C++ tests would not compile. "I've never been very good at decoding GCC's error messages," he admits, "so if I couldn't fix a test with a trivial modification, I didn't include it in my benchmarks."

Lea also modified one of the tests, the string concatenation test for Java.

"The test was creating a new StringBuffer in each iteration of the loop, which was just silly," he explains. "I updated the code to use a single StringBuffer and appending to it inside the loop."

(The updated tests at the original shootout use this new method.)

"Java lost this benchmark even with the modifications," Lea declares. "So if anyone wants to accuse me of biasing the results, they're going to have to try harder."

Several versions of some of the C++ tests (like matrix) were present in the original shootout source, he continues. 

"I used the versions without numbers in them, like matrix.g++ instead of matrix.g++2. I don't know which of these were used in the original benchmarks, but from my quick experimenting, the numberless ones generally ran faster than their numbered counterparts."

"Looking at them again," Lea says, "matrix.g++3 runs faster than the matrix.g++ that I use. However, it still runs slower than the Java version, so I don't plan to modify the graph/data unless someone asks me to, since getting that graph in the first place was sort of a pain.)"

He continues: "I've been told that the C++ code for the Method Call benchmark returns by value while the Java code returns by reference, and that modifying the C++ code to pass a pointer makes that benchmark faster. However, even with the modification, the C++ version still runs slower than the Java version."

Lea ran the tests many times before running the "official" recorded set of tests, so there was plenty of time for both Java and the C++ tests to "warm up" (both the Java and C++ tests got faster after he ran them a few times).

"I've been told that these tests are invalid because they were run with GCC," he concedes, adding: "I have seen both benchmarks that show GCC producing faster code than Visual Studio's VC++ compiler, and benchmarks showing the opposite. If I update the benchmarks with another compiler added, it will be the Intel C++ Compiler, which I'm pretty sure produces faster code than VC++."

Lea says he's been accused of biasing the results by using the -O2 option for GCC, "supposedly because -O2 optimizes for space, thus slowing down the benchmark," he explains.

But this is not what -O2 does, he points out, referring to the GCC -O documentation:

-O2: Optimize even more. GCC performs nearly all supported optimizations that do not involve a space-speed tradeoff. The compiler does not perform loop unrolling or function inlining when you specify -O2. As compared to -O, this option increases both compilation time and the performance of the generated code.

"On the other hand, -O3 performs space-speed tradeoffs, and -O performs fewer optimizations. Thus, for these tests, I think O2 was the best choice," Lea concludes.

 

"I don't have an automated means of building and benchmarking these things (and the scripts that came with the original shootout didn't run for me)," he continues. "I really do want people to test it on their own machines, but it's going to take some work, I guess."

Lea compiled the C++ code with:

g++ [test].cpp -O2 -march=i386 -o [test]-386

g++ [test].cpp -O2 -march=i686 -o [test]-686

and the Java code with:

javac [test].java

To see how he ran the binaries, see the run log. You can download the source code he used in either .bz2 or .zip format.

Using the Server JVM

Every form of Sun's Java runtime comes with both the "client VM" and the "server VM."

"Unfortunately, Java applications and applets run by default in the client VM," Lea observes. "The Server VM is much faster than the Client VM, but it has the downside of taking around 10% longer to start up, and it uses more memory."

Lea explains the two ways to run Java applications with the server VM as follows

  1. When launching a Java application from the command line, use java -server [arguments...] instead of java [arguments...]. For example, use java -server -jar beanshell.jar.
  2. Modify the jvm.cfg file in your Java installation. (It's a text file, so you can use Notepad or Emacs to edit it.) This is located in C:\Program Files\Java\j2reXXX\lib\i386\ on Windows, /usr/java/j2reXXX/lib/i386/ on Linux. You will see two lines:
    -client KNOWN
    -server KNOWN
    You should change them to:
    -server KNOWN
    -client KNOWN
    This change will cause the server VM to be run for all applications, unless they are run with the -client argument.

He can be contacted at

Every form of Sun's Java runtime comes with both the "client VM" and the "server VM."

"Unfortunately, Java applications and applets run by default in the client VM," Lea observes. "The Server VM is much faster than the Client VM, but it has the downside of taking around 10% longer to start up, and it uses more memory."

Lea explains the two ways to run Java applications with the server VM as follows

  1. When launching a Java application from the command line, use java -server [arguments...] instead of java [arguments...]. For example, use java -server -jar beanshell.jar.
  2. Modify the jvm.cfg file in your Java installation. (It's a text file, so you can use Notepad or Emacs to edit it.) This is located in C:\Program Files\Java\j2reXXX\lib\i386\ on Windows, /usr/java/j2reXXX/lib/i386/ on Linux. You will see two lines:
    -client KNOWN
    -server KNOWN
    You should change them to:
    -server KNOWN
    -client KNOWN
    This change will cause the server VM to be run for all applications, unless they are run with the -client argument.

He can be contacted at [email protected].

Links

More Stories By Jeremy Geelan

Jeremy Geelan is Chairman & CEO of the 21st Century Internet Group, Inc. and an Executive Academy Member of the International Academy of Digital Arts & Sciences. Formerly he was President & COO at Cloud Expo, Inc. and Conference Chair of the worldwide Cloud Expo series. He appears regularly at conferences and trade shows, speaking to technology audiences across six continents. You can follow him on twitter: @jg21.

Comments (152)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


IoT & Smart Cities Stories
Dion Hinchcliffe is an internationally recognized digital expert, bestselling book author, frequent keynote speaker, analyst, futurist, and transformation expert based in Washington, DC. He is currently Chief Strategy Officer at the industry-leading digital strategy and online community solutions firm, 7Summits.
Digital Transformation is much more than a buzzword. The radical shift to digital mechanisms for almost every process is evident across all industries and verticals. This is often especially true in financial services, where the legacy environment is many times unable to keep up with the rapidly shifting demands of the consumer. The constant pressure to provide complete, omnichannel delivery of customer-facing solutions to meet both regulatory and customer demands is putting enormous pressure on...
IoT is rapidly becoming mainstream as more and more investments are made into the platforms and technology. As this movement continues to expand and gain momentum it creates a massive wall of noise that can be difficult to sift through. Unfortunately, this inevitably makes IoT less approachable for people to get started with and can hamper efforts to integrate this key technology into your own portfolio. There are so many connected products already in place today with many hundreds more on the h...
The standardization of container runtimes and images has sparked the creation of an almost overwhelming number of new open source projects that build on and otherwise work with these specifications. Of course, there's Kubernetes, which orchestrates and manages collections of containers. It was one of the first and best-known examples of projects that make containers truly useful for production use. However, more recently, the container ecosystem has truly exploded. A service mesh like Istio addr...
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Charles Araujo is an industry analyst, internationally recognized authority on the Digital Enterprise and author of The Quantum Age of IT: Why Everything You Know About IT is About to Change. As Principal Analyst with Intellyx, he writes, speaks and advises organizations on how to navigate through this time of disruption. He is also the founder of The Institute for Digital Transformation and a sought after keynote speaker. He has been a regular contributor to both InformationWeek and CIO Insight...
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
To Really Work for Enterprises, MultiCloud Adoption Requires Far Better and Inclusive Cloud Monitoring and Cost Management … But How? Overwhelmingly, even as enterprises have adopted cloud computing and are expanding to multi-cloud computing, IT leaders remain concerned about how to monitor, manage and control costs across hybrid and multi-cloud deployments. It’s clear that traditional IT monitoring and management approaches, designed after all for on-premises data centers, are falling short in ...
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...