Question

Our compiler is clever about avoiding unnecessary stack operations, but it is not clever at all when it comes to compiling calls to the primitive procedures of the language in terms of the primitive operations supplied by the machine. For example, consider how much code is compiled to compute \((+a 1):\) The code sets up an argument list in argl, puts the primitive addition procedure (which it finds by looking up the symbol + in the environment) into proc, and tests whether the procedure is primitive or compound. The compiler always generates code to perform the test, as well as code for primitive and compound branches (only one of which will be executed). We have not shown the part of the controller that implements primitives, but we presume that these instructions make use of primitive arithmetic operations in the machine's data paths. Consider how much less code would be generated if the compiler could open-code primitives-that is, if it could generate code to directly use these primitive machine operations. The expression (+ a 1) might be compiled into something as simple as \({ }^{43}\) (assign val (op lookup-variable-value) (const a) (reg env)) (assign val (op +) (reg val) (const 1)) In this exercise we will extend our compiler to support open coding of selected primitives. Special-purpose code will be generated for calls to these primitive ;; construct the procedure and skip over code for the procedure body (assign val (op make-compiled-procedure) (label entry2) (reg env)) (goto (label after-lambda1)) entry2 ;calls to factorial will enter here (assign env (op compiled-procedure-env) (reg proc)) (assign env (op extend-environment) (const (n)) (reg argl) (reg env)) begin actual procedure body (save continue) (save env) ;; compute (=n 1) (assign proc (op lookup-variable-value) (const =) (reg env)) (assign val (const 1)) (assign argl (op list) (reg val)) (assign val (op lookup-variable-value) (const n) (reg env)) (assign argl (op cons) (reg val) (reg argl)) (test (op primitive-procedure?) (reg proc)) (branch (label primitive-branch17)) compiled-branch16 (assign continue (label after-calli5)) (assign val (op compiled-procedure-entry) (reg proc)) (goto (reg val)) primitive-branch17 (assign val (op apply-primitive-procedure) (reg proc) (reg argl)) after-callis ; val now contains result of \((=\mathrm{n} 1)\) (restore env) (restore continue) (test (op false?) (reg val)) (branch (label false-branch4)) true-branch5 ; return 1 (assign val (const 1)) (goto (reg continue)) false-branch4 ;; compute and return (* (factorial (- n 1)) n) (assign proc (op lookup-variable-value) (const *) (reg env)) (save continue) (save proc) ; save* procedure (assign val (op lookup-variable-value) (const n) (reg env)) (assign argl (op list) (reg val)) (save argl) ; save partial argument list for * ;; compute (factorial (- n 1)), which is the other argument for* (assign proc (op lookup-variable-value) (const factorial) (reg env)) (save proc) ; save factorial procedure

Short answer

Implement open coding to reduce overhead by directly emitting machine operations for primitives.

Step-by-step solution

Understanding the problem

The problem is about optimizing the compilation of primitive operations like "+" by directly emitting machine code for such operations, avoiding the overhead of general procedure calls.

Current Compilation Process

Currently, the compiler generates code to handle both primitive and compound operations, which involves setting up an argument list, looking up procedures in the environment, and testing the procedure type.

Efficient Compilation via Open Coding

Open-coding means generating direct machine operations for known primitives like addition. Instead of using generic setup and procedure calls, we emit specific machine instructions directly where possible.

Example Compilation with Open Coding

For an expression like "+ a 1", open coding would directly translate it to something like: (assign val (op lookup-variable-value) (const a) (reg env)) (assign val (op +) (reg val) (const 1)) This bypasses the need for argument lists and proc lookups.

Implementing Open Coding

Extend the compiler by adding checks for known primitive procedures during compilation, and directly emit the appropriate machine instructions for them, skipping the standard procedure call setup.

Key concepts

Primitive Operations

Primitive operations refer to the basic operations provided by a computer's architecture. These operations are fundamental, often involving simple arithmetic such as addition, subtraction, multiplication, or division that can be executed directly by the machine's hardware without needing further breakdown. In compilers, especially those dealing with high-level programming languages, harnessing these primitive operations effectively is key to performance, as they can be executed very quickly. Tackling optimizations like reducing unnecessary procedure calls for operations that are primitive allows the code to execute faster and with less overhead because the operations are handled at a low level by the machine itself.

• Primitive operations are directly supported by the hardware.
• They form the building blocks for more complex operations in the machine.
• Efficient use of primitives can lead to significant performance enhancements.

When writing a compiler or trying to understand compiler optimizations, it's important to recognize how these primitive operations are used by the machine and how they can be accessed directly to improve code execution.

Open Coding

Open coding, also known as inline coding, is a compiler optimization technique. It involves transforming a high-level language construct, typically a call to a primitive operation, directly into the corresponding machine instructions. Rather than generating general call instructions that might involve setting up arguments and procedure type checks, open coding inserts the exact machine operations needed. This allows for more efficient execution of common operations.

• Open coding eliminates the need for certain procedure call overheads.
• It allows compilers to insert straight-line code, fostering faster execution.
• Common examples include arithmetic operations directly coded into machine instructions, bypassing the need for additional setup.

This method is beneficial in scenarios where the operation being performed is simple and frequent. For example, instead of generating code that calls a generic addition function, the compiler directly produces the machine instruction for addition, which speeds up execution and reduces resource use. It's a trade-off between general-purpose flexibility and execution efficiency, well worth it for repeated or simple operations.

Procedure Calls

Procedure calls in programming involve invoking a sequence of commands, typically managed as a single, reusable function. This mechanism is central to modular programming, enabling code reuse and abstraction. However, in the context of compiling, procedure calls can introduce overhead. They often require setting up call stacks, managing return addresses, preparing argument lists, and determining the procedure type—all of which can slow down program execution.

• Procedure calls offer modularity and reusability at the cost of some execution speed.
• They require stack operations to manage parameters and return addresses.
• Compilers can optimize calls by open coding to reduce this overhead when dealing with simple operations.

In compiler optimization, minimizing the number of explicit procedure calls, especially for primitive operations, leads to more efficient execution. Instead of going through the usual procedure setup for operations like addition, multiplication, or checking a condition, a compiler can use open coding to bypass these steps, aligning more closely with the machine's native operations. This results in less complex and faster-executing code.