Various optimizations passes leveraging the LLVM IR.

This repository contains a standalone version of the optimization passes, tested for LLVM 17.0.6. A full version of LLVM's source code, with our passes plugged-in, can be found here.

Implementare tre passi LLVM (dentro lo stesso passo LocalOpts già scritto durante il LAB 2) che realizzano le seguenti ottimizzazioni locali:

1. Algebraic Identity

   • $x + 0 = 0 + x \Rightarrow x$
   • $x \times 1 = 1 \times x \Rightarrow x$

2. Strength Reduction (più avanzato)

   • $15 \times x = x \times 15 \Rightarrow (x << 4) – x$
   • $y = x / 8 ⇒ y = x >> 3$

3. Multi-Instruction Optimization

   • $a = b + 1, c = a − 1 ⇒ a = b + 1, c = b$

The testing directory tree looks like this:

testing
├── expected
│   ├── advanced_pow2_sr_expected.ll
│   ├── algebraic_id_expected.ll
│   ├── basic_pow2_sr_expected.ll
│   ├── edge_cases_expected.ll
│   └── multi_instr_expected.ll
├── optimized
│   ├── advanced_pow2_sr_optimized.ll
│   ├── algebraic_id_optimized.ll
│   ├── basic_pow2_sr_optimized.ll
│   ├── edge_cases_optimized.ll
│   └── multi_instr_optimized.ll
└── tests
    ├── advanced_pow2_sr.ll
    ├── algebraic_id.ll
    ├── basic_pow2_sr.ll
    ├── edge_cases.ll
    └── multi_instr.ll

Where:

• tests -> contains some samples of IR code to check if our opt passes work
• expected -> contains the expected outcome, our desired results that our opt passes should reach
• optimized -> contains the IR code generated with our opt passes

the bash script testing.sh automatically generates all the optimized.ll and put them in optimized files for every test in tests.

It also checks if every expected.ll and optimized.ll are equal, and if it's true, the test is passed.

• Type definitions (classes, structs, and so on) -> PascalCase
• Methods -> camelCase
• Variables -> camelCase

Tabs must be expanded as 2 spaces.

For each of the following three analysis problems:

1. Derive a formalization for the Dataflow Analysis framework, filling in the table with the appropriate
   parameters:

   • Domain
   • Direction
   • Transfer Function
   • Meet Operator
   • Boundary Condition
   • Initial interior points

2. For the provided example CFG, populate a table with the iterations of the iterative algorithm solving the problem:

Starting from the code of the previous exercise, implement a step of Loop-Invariant Code Motion (LICM).

• Do not use the acronym LICM for the step.

• It would conflict with the official LLVM step.

• Move the instructions that are not dependent on the loop's control flow out of the loop itself.

• Avoid redundantly recalculating the same thing.

• Since the bulk of a program's computation is contained within loops, there is enormous potential for performance improvement.

Which instructions are loop-invariant in this example?

graph TD
    A[Header] -->B[A = B + C
                   F = A + 2]
    A[Header] -->C[E = 3]
    C -->D[A = 1]
    B -->D
    C -->E[outside loop]
    D -- YES-> B, C are defined outside of the loop -->A
   

• code motion: with this practice we move loop invariant instructions inside the preheader block

Observations:

• Loop-invariant instructions
  • Operands are defined outside the loop or through instructions that are loop-invariant
• Code motion
  • Not all loop-invariant instructions can be moved into the preheader

Algorithm (three macro phases):

• We find the loop-invariant instructions
• We verify that the conditions for code motion are met
• We move the instructions

Conditions for Code Motion:

• General conditions (applicable to all transformations):
• Correctness: Code movement does not alter the semantics of the program
• Performance: The execution of the code is not slowed down

Given a set of nodes in a loop:

• Calculate the reaching definitions
• Find the loop-invariant instructions
• Compute the dominators (dominance tree)
• Find the loop exits (successors outside the loop)
• Instructions eligible for code motion:
  • They are loop invariant
  • They are located in blocks that dominate all loop exits
  • They assign a value to variables not assigned elsewhere in the loop
  • They are located in blocks that dominate all blocks in the loop using the variable to which a value is being assigned
• Perform a depth-first search of the blocks
  • Move the candidate instruction to the preheader if all invariant instructions on which it depends have been moved

• Christofer Fanò [@ch-fano]
• Francesco Mecatti [@mc-cat-tty]
• Antonio Stano [@ent0n29]

MIT