Develop a static analysis tool using LLVM/Clang to identify functions in C/C++ code that exhibit data parallelism, i.e. performing the same operation on independent data elements. The tool should emit a diagnostic message for each function demonstrating data parallelism.

Key Tasks

• Introduce a new command-line option (e.g., -analyze-data-parallelism) to enable the data parallelism analysis.
• Define what constitutes data parallelism (e.g., independent iterations of loops).
• Determine patterns and indicators of data parallelism in LLVM IR.
• Identify loops and determine if iterations are independent (i.e., no data dependencies).
• Emit diagnostics for functions with data parallelism, explaining the detected data parallelism.

Example(s)
Data Parallelism

void compute(float* data, int N) {
    for (int i = 0; i < N; ++i) {
        data[i] = sin(data[i]) + cos(data[i]);
    }
}

No Data Parallelism

void process(float* data, int N) {
    for (int i = 0; i < N; ++i) {
        if (data[i] > 0) {
           data[i] = sqrt(data[i]);
        }
    }
}

Expected Output
Function 'compute' has data parallelism: - Independent loop iterations detected at line 42