Grug Locals & Globals: Moving Ownership To Backend For Efficiency

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Grug Locals & Globals: Moving Ownership to Backend for Efficiency

Hey guys! Today, we're diving deep into a discussion about optimizing Grug, especially when it interacts with non-native languages like Java and JavaScript. We're tackling the challenge of managing Grug objects and how to make things smoother and more efficient. So, let's get started!

The Challenge with Non-Native Languages and Grug

When using non-native languages with Grug, particularly those that require a Foreign Function Interface (FFI) to interact with grug.so, we encounter some interesting hurdles. Think of languages like Java (using JNI) and JavaScript (with Node.js runtime). These languages often need to pass temporary arrays of local bytes for each function call. Let's break down why this happens and the implications.

Understanding the Temporary Array Issue

The core issue arises from how these non-native languages handle memory and object management compared to Grug's native environment. In the provided Java example, you can see this in action:

List<GrugObject> oldFnEntities = Grug.fnEntities;
Grug.fnEntities = new ArrayList<>();

GrugModLoader.grug.BlockEntity_on_tick(grugEntity.onFns, grugEntity.globals);

Grug.fnEntities = oldFnEntities;

Here, a temporary ArrayList is created to manage GrugObject instances. The original Grug.fnEntities is saved, a new empty list is created, the Grug function (BlockEntity_on_tick) is called, and then the original list is restored. This dance is necessary because the Grug functions might modify the list of entities, and we need to isolate these changes within the scope of the function call. This approach ensures that each function call has its own isolated environment, preventing unintended side effects.

The Initial Approach and Its Pitfalls

Initially, Grug.fnEntities was designed as a static variable to optimize performance by reusing the same list across multiple function calls. The idea was to avoid the overhead of creating a new list every time. However, this approach led to some nasty bugs, especially when functions indirectly called other functions, like this:

on_tick() {
    // Calls foo's on_spawn()
    spawn_foo()
}

In this scenario, if on_tick() calls spawn_foo(), and spawn_foo() also interacts with Grug.fnEntities, the static list could become corrupted. The changes made by spawn_foo() might interfere with the state expected by on_tick(), leading to unexpected behavior and crashes. To mitigate this, the stack push and pop approach was introduced.

The Stack Push and Pop Solution

The lines Grug.fnEntities = new ArrayList<>(); and Grug.fnEntities = oldFnEntities; together act like a stack push and pop mechanism. Before a Grug function is called, the current state of Grug.fnEntities is effectively pushed onto a stack (by saving the reference in oldFnEntities and creating a new list). After the function call, the original state is popped from the stack (by restoring Grug.fnEntities to oldFnEntities).

This mechanism ensures that each function call operates on its own isolated list of entities, preventing the kind of interference that plagued the static list approach. It's a clever way to manage state in a concurrent environment, but it comes with its own overhead. Creating and destroying lists frequently can be expensive, especially in performance-sensitive applications.

Moving the Stack Management to the Grug Backend

So, where do we go from here? The current solution works, but it's not the most efficient. My initial plan was to hide the Grug.fnEntities = new ArrayList<>(); line within the bindings, making the Java code cleaner. However, a more intriguing possibility has emerged: could the Grug backend itself handle this push and pop mechanism directly on the native stack?

Benefits of Backend Stack Management

Moving the stack management to the Grug backend could offer several advantages:

  1. Performance: The Grug backend, being closer to the metal, might be able to perform stack operations more efficiently than the bindings in non-native languages. Native stack operations are generally faster than creating and destroying managed objects in languages like Java.
  2. Consistency: By centralizing the stack management in the backend, we ensure consistent behavior across all non-native language bindings. This reduces the risk of subtle differences and bugs arising from different implementations in each binding.
  3. Simplicity: It could simplify the bindings code, making it easier to maintain and less prone to errors. The bindings would no longer need to worry about the intricacies of stack management, allowing them to focus on the core task of interfacing with Grug functions.

How Could This Work?

The basic idea is that the Grug backend would maintain a stack of GrugObject lists. Before a function call, it would push the current list onto the stack and create a new empty list. After the function call, it would pop the previous list from the stack, restoring the state. This could potentially be implemented using native stack operations, which are highly optimized for this kind of task.

Potential Challenges and Considerations

Of course, this approach isn't without its challenges. We need to consider:

  • Memory Management: How will the backend manage the memory for the stack of lists? We need to ensure that memory is allocated and deallocated efficiently to avoid leaks and performance issues.
  • Concurrency: If Grug functions are called concurrently from multiple threads, we need to ensure that the stack operations are thread-safe. This might require the use of locks or other synchronization mechanisms.
  • Complexity: Moving the stack management to the backend adds complexity to the Grug core. We need to carefully weigh the benefits against the increased complexity and potential for bugs.

Exploring Alternatives and Optimizations

Before we commit to this approach, it's worth exploring other alternatives and optimizations. For example, could we use a pool of pre-allocated lists instead of creating and destroying them on demand? This could reduce the overhead of memory allocation and deallocation. Or, could we use a more efficient data structure for storing the list of entities, such as a linked list or a sparse array?

Community Input and Collaboration

This is where you guys come in! I'm eager to hear your thoughts and ideas on this. Do you see any potential issues with moving the stack management to the backend? Do you have any suggestions for alternative approaches or optimizations? Let's collaborate and find the best solution for Grug!

Sharing Your Thoughts and Experiences

Have you encountered similar challenges in other projects? How did you solve them? Sharing your experiences can help us learn from each other and make better decisions. Whether you're a seasoned Grug developer or just starting out, your input is valuable.

Contributing to the Discussion

Feel free to leave your comments, suggestions, and questions below. Let's have a constructive discussion and explore the best way to optimize Grug's interaction with non-native languages. Together, we can make Grug even more powerful and efficient!

Conclusion: Optimizing Grug for the Future

In conclusion, optimizing Grug's interaction with non-native languages is a crucial step in its evolution. The challenge of managing Grug objects, particularly when dealing with function calls across language boundaries, requires careful consideration and innovative solutions. Moving the stack management to the Grug backend is a promising approach that could offer significant performance and consistency benefits.

The Journey Ahead

However, as with any major architectural change, we need to proceed thoughtfully and thoroughly. Exploring alternative solutions, addressing potential challenges, and leveraging community input are essential steps in ensuring that we make the right decision for Grug's future. By working together and sharing our expertise, we can build a more robust, efficient, and versatile Grug ecosystem.

Embracing Collaboration and Innovation

The journey of optimizing Grug is an ongoing process, one that requires collaboration, innovation, and a willingness to challenge assumptions. Let's continue to explore new ideas, experiment with different approaches, and learn from each other. Together, we can unlock Grug's full potential and create a truly exceptional language.

So, let's keep the conversation going! Share your thoughts, ask questions, and contribute your ideas. The future of Grug is in our hands, and together, we can make it bright!