When we need to do a suspend check, we clear the pointer and once it becomes visible to the thread the first LDR rX, will load null and the second will segfault. As long as we don't need to do a suspend check, we keep that self-pointing pointer. Going into a bit more detail, a reserved register rX is pre-loaded with an address within the thread where we have a pointer pointing to itself. We would load the value, test it, and branch into the safepoint if needed. The previous implementation was an explicit boolean check. When a safepoint call is issued, the threads must go into a safepoint and are blocked until they are released. Safepoints are used for many reasons, the most important of them being Garbage Collection. Suspend checks are safepoints (represented by the houses in the image below) where we can pause the thread execution. Let's assume we have several threads running. Implementing this new pass contributes to 0.8% code size reduction. In the following example, we can't guarantee a GC won't need to examine or modify the tracking information between the modifications: If an instruction may trigger a GC (for example, Invokes and SuspendChecks), we wouldn't be able to eliminate write barriers. Previously, we would emit a write barrier for each object modification but we only need a single write barrier because: 1) the mark will be set in o itself (and not in the inner objects), and 2) a garbage collection can't have interacted with the thread between those sets. For example, Constant Folding is an optimization that tries to replace instructions with constant values like folding the addition operation 2 + 3 into a 5. The optimization pipeline has phases that execute in order that each concentrate on a particular set of optimizations. The last step of the pipeline is a code generation phase where dex2oat converts the IR into native code (for example, AArch64 assembly). Using the IR, dex2oat performs a number of code optimizations. The first step is to parse the DEX code and generate an Intermediate Representation (IR). We can have our upside-down cake and eat it too! Optimizing compiler 101ĪRT compiles applications from the DEX format to native code using the on-device dex2oat tool. They are available through the ART mainline update so you don’t even need a full OS update to reap the benefits. Since ART has been updateable from Android 12, these optimizations reach 1B+ devices for whom we are saving 47-95 petabytes (47-95 millions of GB!) globally!Īll the improvements mentioned in this blog post are open source. This could be just the thing you need to be able to update your favorite app, or download a new one. With the new release of ART, we estimate saving users about 50-100MB per device. In this blog post we will talk about optimizations that reduce code size without impacting performance.Ĭode size is one of the key metrics we look at, since smaller generated files are better for memory (both RAM and storage). Improving ART makes the system and user-experience better as a whole, as it is the common denominator in Android apps. We constantly improve ART to generate smaller and more performant code. The Android Runtime (ART) executes Dalvik bytecode produced from apps and system services written in the Java or Kotlin languages. Posted by Santiago Aboy Solanes - Software Engineer
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