This section explains a few concepts related to LLVM, not specific to llvmpy.
The intermediate representation, or IR for short, is an in-memory data structure that represents executable code. The IR data structures allow for creation of types, constants, functions, function arguments, instructions, global variables and so on. For example, to create a function sum that takes two integers and returns their sum, we need to follow these steps:
create an integer type ti of required bitwidth
create a function type tf which takes two ti -s and returns another ti
create a function of type tf named sum
add a basic block to the function
using a helper object called an instruction builder, add two instructions into the basic block:
- an instruction to add the two arguments and store the result into a temporary variable
- a return instruction to return the value of the temporary variable
(A basic block is a block of instructions.)
LLVM has it’s own instruction set; the instructions used above (add and ret) are from this set. The LLVM instructions are at a higher level than the usual assembly language; for example there are instructions related to variable argument handling, exception handling, and garbage collection. These allow high-level languages to be represented cleanly in the IR.
All LLVM instructions are represented in the Static Single Assignment (SSA) form. Essentially, this means that any variable can be assigned to only once. Such a representation facilitates better optimization, among other benefits.
A consequence of single assignment are PHI (Φ) nodes. These are required when a variable can be assigned a different value based on the path of control flow. For example, the value of b at the end of execution of the snippet below:
a = 1;
if (v < 10)
a = 2;
b = a;
cannot be determined statically. The value of ‘2’ cannot be assigned to the ‘original’ a, since a can be assigned to only once. There are two a ‘s in there, and the last assignment has to choose between which version to pick. This is accomplished by adding a PHI node:
a1 = 1;
if (v < 10)
a2 = 2;
b = PHI(a1, a2);
The PHI node selects a1 or a2, depending on where the control reached the PHI node. The argument a1 of the PHI node is associated with the block “a1 = 1;” and a2 with the block “a2 = 2;”.
PHI nodes have to be explicitly created in the LLVM IR. Accordingly the LLVM instruction set has an instruction called phi.
The LLVM IR can be represented offline in two formats
All three formats (the in-memory IR, the LLVM assembly language and the LLVM bitcode) represent the same information. Each format can be converted into the other two formats (using LLVM APIs).
The LLVM demo page lets you type in C or C++ code, converts it into LLVM IR and outputs the IR as LLVM assembly language code.
Just to get a feel of the LLVM assembly language, here’s a function in C, and the corresponding LLVM assembly (as generated by the demo page):
/* compute sum of 1..n */
unsigned sum(unsigned n) {
if (n == 0)
return 0;
else
return n + sum(n-1);
}
The corresponding LLVM assembly:
; ModuleID = '/tmp/webcompile/_7149_0.bc'
target datalayout = "e-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-f32:32:32-f64:64:64-v64:64:64-v128:128:128-a0:0:64-s0:64:64-f80:128:128-n8:16:32:64"
target triple = "x86_64-linux-gnu"
define i32 @sum(i32 %n) nounwind readnone {
entry:
%0 = icmp eq i32 %n, 0 ; [#uses=1]
br i1 %0, label %bb2, label %bb1
bb1: ; preds = %entry
%1 = add i32 %n, -1 ; [#uses=2]
%2 = icmp eq i32 %1, 0 ; [#uses=1]
br i1 %2, label %sum.exit, label %bb1.i
bb1.i: ; preds = %bb1
%3 = add i32 %n, -2 ; [#uses=1]
%4 = tail call i32 @sum(i32 %3) nounwind ; [#uses=1]
%5 = add i32 %4, %1 ; [#uses=1]
br label %sum.exit
sum.exit: ; preds = %bb1.i, %bb1
%6 = phi i32 [ %5, %bb1.i ], [ 0, %bb1 ] ; [#uses=1]
%7 = add i32 %6, %n ; [#uses=1]
ret i32 %7
bb2: ; preds = %entry
ret i32 0
}
Note the usage of SSA form. The long string called target datalayout is a specification of the platform ABI (like endianness, sizes of types, alignment etc.).
The LLVM Language Reference defines the LLVM assembly language including the entire instruction set.
Modules, in the LLVM IR, are similar to a single C language source file (.c file). A module contains:
Modules are top-level containers; all executable code representation is contained within modules. Modules may be combined (linked) together to give a bigger resultant module. During this process LLVM attempts to reconcile the references between the combined modules.
LLVM provides quite a few optimization algorithms that work on the IR. These algorithms are organized as passes. Each pass does something specific, like combining redundant instructions. Passes need not always optimize the IR, it can also do other operations like inserting instrumentation code, or analyzing the IR (the result of which can be used by passes that do optimizations) or even printing call graphs.
This LLVM documentation page describes all the available passes, and what they do.
LLVM does not automatically choose to run any passes, anytime. Passes have to be explicitly selected and run on each module. This gives you the flexibility to choose transformations and optimizations that are most suitable for the code in the module.
There is an LLVM binary called opt, which lets you run passes on bitcode files from the command line. You can write your own passes (in C/C++, as a shared library). This can be loaded and executed by +opt+. (Although llvmpy does not allow you to write your own passes, it does allow you to navigate the entire IR at any stage, and perform any transforms on it as you like.)
A “pass manager” is responsible for loading passes, selecting the correct objects to run them on (for example, a pass may work only on functions, individually) and actually runs them. opt is a command-line wrapper for the pass manager.
LLVM defines two kinds of pass managers:
LLVM IR can be represented as a bitcode format for disk storage. It is suitable for fast loading by JIT compiler. See LLVM documentation for detail about the bitcode format.
The execution engine implements execution of LLVM IR through an interpreter or a JIT dynamic compiler. An execution engine can contain multiple modules.
Note
Inter-module reference is not possible. That is module A cannot call a function in module B, directly.