Summary
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Implement a Java 2D internal rendering pipeline for macOS using the Apple Metal API as alternative to the existing pipeline, which uses the deprecated Apple OpenGL API.
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Goals
- Superstar makeover mac os. Provide a fully functional rendering pipeline for the Java 2D API that uses the macOS Metal framework.
- Be ready in the event Apple removes the deprecated OpenGL API from a future version of macOS.
- Ensure transparency of the new pipeline to Java applications.
- Ensure functional parity of the implementation with the existing OpenGL pipeline.
- Provide performance as good or better than the OpenGL pipeline in select real applications and benchmarks.
- Create a clean architecture that fits into the existing Java 2D pipeline model.
- Co-exist with the OpenGL pipeline until it is obsolete.
Non-Goals
- It is not a goal to remove or disable the existing OpenGL pipeline.
- It is not a goal to add any new Java or JDK APIs. This is all internal implementation.
Motivation
Two major factors motivate the introduction of a new Metal-based rendering pipeline on macOS:
- Apple deprecated the OpenGL rendering library in macOS 10.14, in September 2018. Java 2D on macOS is completely reliant on OpenGL for its internal rendering pipeline, so a new pipeline implementation is needed.
- Apple claims that the Metal framework, their replacement for OpenGL, has superior performance. For the Java 2D API, this is generally the case with some exceptions.
Description
Most graphical Java applications are written using the Swing UI toolkit, which renders via the Java 2D API. Internally, Java 2D can use software rendering plus a blit to the screen or it can use a platform-specific API, such as X11/Xrender on Linux, Direct3D on Windows, or OpenGL on macOS. These platform-specific APIs typically offer much better performance than software rendering, and generally off-load the CPU. Metal is the new macOS platform API for such rendering, replacing the deprecated OpenGL API. (The name has nothing to do with the Swing “Metal” Look and Feel; that is just a coincidence.)
We created a substantial amount of new internal implementation code to use the Metal framework, just as we already had for the other platform-specific APIs. Whilst easily fitting into the existing framework the new code is much more modern in its use of graphics hardware, making use of shaders rather than a fixed function pipeline.The changes are confined to macOS-specific code and even there only a minimal amount of code shared between Metal and OpenGL is updated. We did not introduce any new Java APIs, nor did we change any existing API.
The Metal pipeline can co-exist with the OpenGL pipeline. When a graphical application starts up, one or the other is chosen. For now, OpenGL remains the default. Metal is used only if it is specified on startup or if the initialization of OpenGL fails, as would happen in a future version of macOS with no OpenGL support.
At the time of integration of this JEP, Apple have yet to remove OpenGL.Until that happens an application can opt-in to Metal by specifying
-Dsun.java2d.metal=true
on the java
command line. We will make the Metal rendering pipeline the default in a future release.Prior to integration in the JDK, we conducted work on this JEP in Project Lanai.
Testing
Testing the functionality of the new pipeline did not require new functional test development, since no Java 2D APIs were changed. Existing tests and real-world applications sufficed. These included:
- JDK jtreg regression tests,
- JCK Tests,
- Java 2D and Swing Demos, and
- IDEs such as Intellij IDEA and Netbeans, as examples of large-scale real world applications.
To test performance, we used:
- J2DBench, a Java 2D benchmarking application included in JDK,
- RenderPerfTest, a custom stress test that renders multiple objects of the same primitive type and measures frames per second (FPS) developed in Project Lanai, and
- IntelliJ IDEA IDE performance.
Performance results for the final planned early-access release are here.
To further verify the new pipeline, we used macOS Xcode instrumentation tools to check for leaks and for correct Metal API usage.
Risks and Assumptions
- We tested on a variety of hardware and macOS versions which are presumed to be representative, but not all combinations were available. Since we could not account for all scenarios, it is possible that performance limitations remain.
- We did very limited (sanity) testing of the current x64 binaries on Apple Silicon. No port of the JDK to Apple Silicon is yet available to support native testing.
- Metal does not support the XOR operation, so we had to accept lower performance in that niche case. That is likely to remain so until such time as Metal provides direct support for XOR.
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Many organizations have working products based on the static build concept, and that approach works just fine for some use cases. However, as Dev and Ops teams move toward a more combined DevOps practice, they’re faced with a major pain point: writing infrastructure to go into ephemeral builds.
Orka has many plugins that allow the use of standard CI tools such as Jenkins, Teamcity, BuildKite, and more (see a full list here). In the event a pipeline is not using a standard CI/CD tool, or the use case is different from normal CI/CD use cases, teams can code their own ephemeral-based architecture using the Orka CLI.
As teams move to virtual machines, they seek to ease a few pain points but find old practices don’t hold up well. For example, one of the old methods with bare metal build machines is a clean-up process to get rid of any artifacts that may interfere with new builds, often followed by a reboot. In VMware, this is replaced with a snapshot revert, and with Orka, this is achieved with a vm delete command followed by vm create, and as of Orka 1.2.0, vm revert has been introduced as another option.
While these pain points can give teams new to infrastructure as code (IaC) pause, the important thing to remember is the workflow changes, but standards do not change. With Orka, the process to start with ephemeral VMs takes as little as two files, but the same general principles apply to VMware and any other system.
At MacStadium, we based our early quality control scripts, and our current Ansible benchmarking scripts, on two key files, an execution file, and basic parser file. This code was written with three conditions:
- Needs to run on any macOS or Linux OS system
- No VM customization beyond installing macOS and enabling SSH
- No extra dependencies could be used on the VM side; staff is allowed to use locally installed dependencies
For these reasons, the benchmarking team chose to use a sh script with AWK. Although it is an older language, AWK conveniently runs on all macOS and Linux OS systems. These files are written against the CLI as opposed to API; this lets the staff do integration testing. However, your team might want to code against the API directly. Harm no human - downloaded version mac os.
Our kick-off script is run-bench.sh and uses six core VMs on Orka:
# Usage: One field, the name of the VM you wish to create and test
# Example: ./run-bench.sh examplevm
orka vm create-config -v $1 -b benchmark.img -c 6 --C 6 -y
# User should see an Orka response at this point
orka vm deploy -v $1 -y
# User should see an Orka response at this point
echo '
# The only json output from the CLI is currently by calling the --json
orka vm list -f all --json > acton.tmp
# Formatting json so awk can read it without a plugin
awk '{tmp=$0;gsub(/ /,'_',tmp);print tmp}' acton.tmp > tmp.tmp
awk '{tmp=$0;gsub(/,/,' ',tmp);print tmp}' tmp.tmp > acton.tmp
# Add in the name of the VM to the awk commands
sed s/nodetest/$1/ benchcommands.awk > run.awk
# Call awk to parse the Orka vm list
awk -f run.awk acton.tmp > comm.sh
chmod +x comm.sh
# Wait for macOS bootup
sleep 30s
# Act on the new VM with random ports
./comm.sh
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And then uses benchcommands.awk Gem rush mac os.
{
# Loop through hte number of fields (NF) on the json output
for (loop = 1; loop
{if ($loop~/nodetest/){name=$loop;
# Find the field with 'virtual_machine_name' and use it to gather data
# Format so 'name' is the VM name, in the above it will be 'examplevm'
sub(/virtual_machine_name../,',name);
gsub(/'/,',name);
# Set the information gathering flags
portflag = 1;
ipflag = 1
}
# Find the Virtual Machine IP of interest inside of the proper VM name
if(($loop~/virtual_machine_ip/)&&(ipflag 1))
{
IP = $loop;
sub(/^.virtual_machine_ip../,',IP);
sub(/.$/,',IP);
ipflag = 0
}
# Find the port of interest, always after the base IP. Output the SSH command.
if((portflag 1)&&($loop~/ssh_port/)){Port = $loop; sub(/.ssh_port../,',Port);
sub(/.$/,',Port)
if((Port~/[a-z]/)||(Port~/[A-Z]/)){}
else {
# known_hosts will often conflict when spinning up multiple VMs on the same base Host IP
print 'mv ~/.ssh/known_hosts garbage.out'
# A simple 'ls' is done here to show success, but any command can be used
print 'ssh -o 'StrictHostKeyChecking no' -p ' Port, ' admin@'IP ' ''ls'';
}
}
}
}
These scripts have a lot of room for customization. Not only can the API be used in place of the CLI, but it is fairly easy to add in extras like opening ports or assigning to specific nodes. Extra feedback can also be quickly added, and more intermediate files can be easily created for bug tracking.
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These two simple scripts have formed the basis for several companies' first steps into infrastructure as code. And these companies have quickly and efficiently innovated on both scripts run from a master as well as those that live on the base image.
Try Orka Yourself
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Want to learn more about Orka? Why not jump right in with our Orka demo? You get a two-hour window to spin up VMs, try the Jenkins plugin, and more! And if you want to stay up to date on the latest on what’s happening at MacStadium, be sure to join the MacStadium Community Slack channel - we post all the latest news to keep you up-to-date on everything we’re doing!