The downsides of JIT compilation
I started reading Crafting Interpreters by Robert Nystrom, author of the other great programming book Game Programming Patterns. At the end of the 2nd chapter, one of the challenge prompts is to figure out why JIT isn’t always the right call, despite it generally providing better runtime performance and portability. Let’s ask the machine.
[What are the downsides of JIT compilation?]
Just-In-Time (JIT) compilation has several advantages, such as improved runtime performance and platform independence, but it also has some downsides:
Overhead: JIT compilation introduces an overhead at the beginning of program execution because it must compile code before it can be executed. This can lead to slower startup times compared to ahead-of-time (AOT) compiled languages.
Memory Usage: JIT compilation often requires more memory during runtime because it needs to store both the compiled code and the original source code. This can be a concern in resource-constrained environments, like embedded systems or mobile devices.
Unpredictable Performance: The performance gains from JIT compilation may not always be consistent. The effectiveness of JIT compilation depends on the quality of the compiler, the runtime environment, and various runtime conditions. This can lead to unpredictable performance characteristics.
Security: JIT compilers can introduce security risks. Since they generate and execute code dynamically, they can potentially be exploited by attackers to inject and execute malicious code. Language runtimes and JIT compilers need to implement strict security measures to mitigate these risks.
Compatibility Issues: JIT compilation may encounter compatibility issues when moving code between different platforms or architectures. Code that is compiled on one system may not work on another, requiring recompilation or adjustments.
Debugging and Profiling: Debugging and profiling JIT-compiled code can be more challenging compared to code compiled ahead of time. Developers may have limited visibility into the generated machine code, making it harder to diagnose issues.
Cold Start Performance: JIT compilation can have a noticeable impact on "cold start" performance, where an application is started for the first time or after a long period of inactivity. The initial compilation can result in slower response times until the code is fully optimized.
Resource Intensive: JIT compilation requires CPU resources to compile code during runtime. In applications with real-time or low-latency requirements, this resource usage can be problematic.
Lack of Determinism: JIT compilation can introduce non-deterministic behavior into an application because the compilation process depends on various factors, including the current state of the system and the compiler's decisions. This can make it harder to reason about and predict program behavior.
Limited Ahead-of-Time Optimization: While JIT compilers can perform dynamic optimizations based on runtime profiling, they may not be able to perform the same level of aggressive optimizations that can be achieved with ahead-of-time (AOT) compilation. AOT compilers have more time to analyze and optimize the code.
Despite these downsides, JIT compilation is a valuable technique in many programming scenarios because it can provide substantial performance improvements and flexibility, especially in dynamic languages or for applications where runtime adaptation is essential. Developers need to weigh the pros and cons of JIT compilation in the context of their specific use cases and requirements.