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Sources of optimization of basic blocks

Optimization of basic blocks involves improving the performance and efficiency of a sequence of consecutive instructions within a program.

Several sources can be explored for optimizing basic blocks.

Some common sources of optimization:

1. Instruction Selection: Choosing the most efficient instructions for each operation within the basic block can have a significant impact on performance. Optimizing instruction selection involves considering factors such as the availability of specialized instructions, efficient addressing modes, and the use of SIMD (Single Instruction, Multiple Data) instructions for parallel processing.

2. Constant Folding and Propagation: Constant folding involves evaluating expressions with constant operands during compile-time rather than at runtime. Constant propagation replaces variables or expressions with constant values whenever possible. Both techniques eliminate unnecessary computations and reduce the number of instructions executed.

3. Common Subexpression Elimination: Common subexpression elimination identifies and removes redundant computations within the basic block. If the same subexpression is computed multiple times, it can be computed once and its result reused, reducing the number of instructions executed.

4. Dead Code Elimination: Dead code elimination identifies and removes instructions that have no impact on the program’s final output. These instructions can be eliminated safely, reducing the execution time and improving overall performance.

5. Register Allocation and Spilling: Efficient register allocation assigns variables to processor registers to minimize memory accesses. Techniques such as register promotion and spilling aim to reduce the number of memory accesses and optimize register usage, improving performance.

6. Loop-Invariant Code Motion (LICM): LICM identifies computations that produce the same result in every iteration of a loop and moves them outside the loop. This optimization eliminates redundant computations and improves the efficiency of loop execution.

7. Strength Reduction: Strength reduction replaces costly operations with cheaper alternatives. For example, replacing multiplication with shifting or replacing division with multiplication. This technique reduces the computational complexity of the basic block and improves performance.

8. Loop Unrolling: Loop unrolling reduces the overhead of loop control and improves instruction-level parallelism by executing multiple iterations of the loop at once. This optimization technique reduces branching and improves cache utilization.

9. Instruction Scheduling: Reordering instructions within the basic block can improve performance by reducing pipeline stalls and maximizing the utilization of execution units. Instruction scheduling aims to minimize idle time and improve the efficiency of instruction execution.

10. Memory Access Optimization: Techniques such as loop blocking or loop tiling can improve cache utilization and reduce memory access latency. By operating on smaller data subsets that fit within the cache, memory access optimization can improve overall performance.

Basic blocks of codes are the number of instructions exist in a source code, which are executed sequentially.

Basic blocks are sequence of codes.

Some of the statements which ends sequence of codes and give born to basic blocks are,

  • If Else
  • Switch Case
  • Do While, etc.

For example:

Take source code as shown below.

a = 0;
b = b+c;
c = 0;
If (a>d)
{
c = b;
b++;
}
else
{
c = d;
d++;
}
a= b+d;

Basic blocks in above source code are

(1)(2)(3)(4)
a = 0;b = b+c;c = 0;c = b;b++;c = d;d++;a= b+d;

Basic blocks are useful in finding repeated variables, used in same basic clock.