[llvm-dev] [LLVMdev] Help with using LLVM to re-compile hot functions at run-time
Revital1 Eres via llvm-dev
llvm-dev at lists.llvm.org
Wed Nov 11 02:44:13 PST 2015
Hi Lang,
Thanks for your reply!
The program I'm compiling is the following toy program which is compiled
with -fno-inline to
avoid inlining foo into main.
In the fully_lazy_with_recompile code I've added the following statements.
When running the
code with gdb I do not see it breaks in the lamda resolver as described in
my previous mail.
auto ExprSymbol = J.findUnmangledSymbolIn(H,"main");
double (*FP)() = (double (*)())(intptr_t)ExprSymbol.getAddress();
std::cerr << "Evaluated to " << FP() << "\n";
Btw, another issue I need to resolve - some of the parameters were
originally read from command line using argv but due to the following
error
I avoided that for now (I also got similar error regarding
ZNSt8ios_base4InitC1Ev when using prints):
LLVM ERROR: Program used external function 'atoi' which could not be
resolved!
Thanks again,
Revital
#define ITERS 1000000
int arr[ITERS];
int
foo (int x, int y)
{
int res = 950;
if (x > 3 && y < 77)
res = 97;
else
res = res * x;
return res;
}
int
main ()
{
int x = 880;
int num = 990;
int i, j;
int b = 0;
for (i = 0; i < ITERS; i++)
arr[i] = i;
for (j = 0; j < num; j++)
for (i = 0; i < ITERS; i++)
{
b += foo (x, arr[i]) /2;
}
return 0;
}
From: Lang Hames <lhames at gmail.com>
To: Revital1 Eres/Haifa/IBM at IBMIL
Cc: LLVM Developers Mailing List <llvm-dev at lists.llvm.org>
Date: 10/11/2015 06:31 PM
Subject: Re: [LLVMdev] Help with using LLVM to re-compile hot
functions at run-time
Hi Revital,
Apologies for the delayed reply - I'm traveling at the moment and not able
to check my email often.
You will only see a callback on the resolver for symbols that are external
to the module. What did the IR that you added look like?
Cheers,
Lang.
On Wed, Nov 4, 2015 at 8:37 AM, Revital1 Eres <ERES at il.ibm.com> wrote:
Hello Lang,
I want to use the lazy recompilation program you posted to compile an
input program RI (not processing the input by
interpreter as it is done in the example).
To do that I called the addModule function on the module returned from
parseInputIR as was done with the other
functions in the Kaleidoscope examples.
Now, to start the codegen I am using getAddress and at this point I was
expecting to see a call to the lamda resolver defined
in createResolver but I did not see it happen and I appreciate your help
to understand why.
Here is a snippet from my additions to the new version of the fully_lazy
Orc Kaleidoscope.
Thanks again,
Revital
SessionContext S(getGlobalContext());
KaleidoscopeJIT J(S);
cl::ParseCommandLineOptions(argc, argv,
"Kaleidoscope example program\n");
std::unique_ptr<Module> M;
if (!InputIR.empty()) {
M = parseInputIR(InputIR);;
auto H = J.addModule(std::move(M));
char ModID[256];
sprintf(ModID, "IR:%s", InputIR.c_str());
auto ExprSymbol = J.findUnmangledSymbolIn(H,ModID);
double (*FP)() = (double (*)())(intptr_t)ExprSymbol.getAddress();
std::cerr << "Evaluated to " << FP() << "\n";
J.removeModule(H);
}
From: Lang Hames <lhames at gmail.com>
To: Revital1 Eres/Haifa/IBM at IBMIL, LLVM Developers Mailing List <
llvm-dev at lists.llvm.org>
Date: 18/09/2015 09:47 AM
Subject: Re: [LLVMdev] Help with using LLVM to re-compile hot
functions at run-time
Hi Revital,
Attached is a new version of the fully_lazy Orc Kaleidoscope demo that has
been extended to enable re-compilation at higher optimisation levels,
roughly following the scheme I outlined before.
In the compile action for the callback, the initial IR for each is
transformed like this:
unsigned foo_counter = 0;
void foo$impl() { void foo$impl() {
// foo body -> if (++foo_counter > 1000) {
} auto fooOpt = $recompile(&foo);
fooOpt();
}
// foo body
}
The key changes to make this work (which you can see by diff'ing toy.cpp
against the original fully_lazy version):
1) New layers HotCompileLayer and HotIROptsLayer added. These perform IR
optimisation and code generation at higher optimisation levels than the
default layers.
2) The symbol resolver function (not to be confused with the resolver
block) has been pulled out into its own function, createResolver, so that
it can be shared between optimised & non-optimized code. It also resolves
the "$recompile" function to a static method on the KaleidoscopeJIT class
itself.
3) The lazy compile action now calls 'instrumentFunctions' before adding
the IR for cold functions to the JIT.
4) The instrumentFunctions method injects the counter code and call to
recompile.
5) The recompileHot method re-IRGens functions, then adds them to the
HotIROpts layer to generate more optimized versions. It then updates the
function-body pointer so that subsequent calls go to the optimised
version.
This is a bit quick-and-dirty, but does work. In the future I'll try to
tidy this up and turn it into a new tutorial chapter.
Hope this helps!
Cheers,
Lang.
On Wed, Sep 16, 2015 at 10:09 PM, Revital1 Eres <ERES at il.ibm.com> wrote:
Hi Lang,
Many thanks!!! I just wanted to make sure you did not miss it...
Thanks again!
Revital
From: Lang Hames <lhames at gmail.com>
To: Revital1 Eres/Haifa/IBM at IBMIL
Cc: LLVM Developers Mailing List <llvmdev at cs.uiuc.edu>
Date: 17/09/2015 01:56 AM
Subject: Re: [LLVMdev] Help with using LLVM to re-compile hot
functions at run-time
Hi Revital,
Apologies for the delayed reply.
I'm working on some example code for how to do this. I'll try to post it
tomorrow.
Cheers,
Lang.
On Tue, Sep 8, 2015 at 12:23 AM, Revital1 Eres <ERES at il.ibm.com> wrote:
Hi Lang,
After spending some time debugging Kaleidoscope orc fully_lazy toy example
on
x86 I want to start implementing run-time optimizer as you suggested and
again
I highly appreciate your help.
For now I'll defer the target specific implementation to the end after
I'll have
the non target parts in place as I can run on x86 as a start.
Given a simple example of main function calling foo and bar functions;
IIUC I should start from the IR level of this module which means that
ParseIRFile will be be first called on the IR of the program, is that
right?
I would like to make sure I understand your suggestion which is to insert
a new
layer that should be implemented on top of the CompileCallbackLayer in
order to
be able to call trigger_condition at the beginning of a function.
IIUC until the function (bar or foo) is optimized the call to foo and bar
will
go through the resolver (foo and bar will not be compiled from scratch
every
time we go through the resolver but rather execute the cached non
optimized
version after first compiled). The resolver will check trigger_condition
to see if the cached non optimized version should be executed or a new
optimizied version should be compiled and executed.
After the trigger_condition is true foo and bar will be compiled to
generate
their optimized version and this version will be executed directly from
now on
(not going through the resolver any more). Is that right?
Does this layer on top of the CompileCallbackLayer should be similar to
class KaleidoscopeJIT?
I saw that in Kaleidoscope Orc's example the Lambda functions that are
added in
createLambdaResolver are been executed by the resolver before compiling a
call
so I assume that the trigger_condition should be added also by
createLambdaResolver so before compiling foo or bar the Lambda functions
that are added by calling createLambdaResolver and contain
trigger_condition
will be executed, is that right?
IIUC in Kaleidoscope Orc's example the interpreter calls the addModule
upon
parsing call expression in HandleTopLevelExpression.
In my case I assume addModule be called for the module returned from
ParseIRFile, right?
In this case should calling getAddress on the whole module (the IR of all
functions) will trigger calling the Lambda functions defined in
createLambdaResolver on foo and bar functions? Also - in Kaleidoscope orc
example the execution of the function is done explicitly in
HandleTopLevelExpression after calling getAddress and its not clear to me
where
I should insert this in my case.
Thanks again,
Revital
From: Lang Hames <lhames at gmail.com>
To: Revital1 Eres/Haifa/IBM at IBMIL
Cc: LLVM Developers Mailing List <llvmdev at cs.uiuc.edu>
Date: 28/07/2015 05:58 AM
Subject: Re: [LLVMdev] Help with using LLVM to re-compile hot
functions at run-time
Hi Revital,
What do you mean by "code cache"? Orc (and MCJIT) does have the concept of
an ObjectCache, which is a long-lived, potentially persistent, compiled
version of some IR. It's not a key component of the JIT though: Most
clients run without a cache attached and just JIT their code from scratch
in each session.
Recompilation is orthogonal to caching. There is no in-tree support for
recompilation yet. There are several ways that it could be supported,
depending on what security / performance trade-offs you're willing to
make, and how deep in to the LLVM code you want to get. As things stand at
the moment all function calls in the lazy JIT are indirected via function
pointers. We want to add support for patchable call-sites, but this hasn't
been implemented yet. The Indirect calls make recompilation reasonably
easy: You could add a transform layer on top of the CompileCallbackLayer
which would modify each function like this:
void foo$impl() { void foo$impl() {
// foo body -> if (trigger_condition) {
} auto fooOpt = jit_recompile_hot(&foo);
fooOpt();
}
// foo body
}
You would implement the jit_recompile_hot function yourself in your JIT
and make it available to JIT'd code via the SymbolResolver. When the
trigger condition is met you'll get a call to recompile foo, at which
point you: (1) Add the IR for foo to a 2nd IRCompileLayer that has been
configured with a higher optimization level, (2) look up the address of
the optimized version of foo, and (3) update the function pointer for foo
to point at the optimized version. The process for patchable callsites
should be fairly similar once they're available, except that you'll
trigger a call-site update rather than rewriting a function pointer.
This neglects all sorts of fun details (threading, garbage collection of
old function implementations), but hopefully it gives you a place to
start.
Regarding laziness, as Hal mentioned you'll have to provide some target
support for PowerPC to support lazy compilation. For a rough guide you can
check out the X86_64 support code in
llvm/include/llvm/ExecutionEngine/Orc/OrcTargetSupport.h and
llvm/lib/ExecutionEngine/Orc/OrcTargetSupport.cpp.
There are two methods that you'll need to implement:
insertCompileCallbackTrampoline and insertResolverBlock. These work
together to enable lazy compilation. Both of these methods inject blobs of
target specific code in to the JIT process. To do this (at least for now)
I make use of a handy feature of LLVM IR: You can write raw assembly code
directly into a bitcode module ("module-level asm"). If you look at the
X86 implementation of each of these methods you'll see they're written in
terms of string-streams building up a string of assembly which will be
handed off to the JIT to compile like any other code.
The first blob that you need to be able to output is the resolver block.
The purpose of the resolver block is to save program state and call back
in to the JIT to trigger lazy compilation of a function. When the JIT is
done compiling the function it returns the address of the compiled
function to the resolver block, and the resolver block returns to the
compiled function (rather than its original return address).
Because all functions share the same resolver block, the JIT needs some
way to distinguish them, which is where the trampolines come in. The JIT
emits one trampoline per function and each trampoline just calls the
resolver block. The return address of the call in each trampoline provides
the unique address that the JIT associates with the to-be-compiled
functions. The CompileCallbackManager manages this association between
trampolines and functions for you, you just need to provide the
resolver/trampoline primitives.
In case it helps, here's what the output of all this looks like on X86.
Trampolines are trivial - they're emitted in blocks and proceeded by a
pointer to the resolver block:
module asm "Lorc_resolve_block_addr:"
module asm " .quad 140439143575560"
module asm "orc_jcc_0:"
module asm " callq *Lorc_resolve_block_addr(%rip)"
module asm "orc_jcc_1:"
module asm " callq *Lorc_resolve_block_addr(%rip)"
module asm "orc_jcc_2:"
module asm " callq *Lorc_resolve_block_addr(%rip)"
...
The resolver block is more complicated and I won't provide the full code
for it here. You can find it by running:
lli -jit-kind=orc-lazy -orc-lazy-debug=mods-to-stderr <hello_world.ll>
and looking at the initial output. In pseudo-asm though, it looks like
this:
module asm "jit_callback_manager_addr:"
module asm " .quad 0x46fc190" // <- address of callback manager object
module asm "orc_resolver_block:"
module asm " // save register state."
module asm " // load jit_callback_manager_addr into %rdi
module asm " // load the return address (from the trampoline call) into
%rsi
module asm " // %rax = call jit(%rdi, %rsi)
module asm " // save %rax over the return address
module asm " // restore register state
module asm " // retq"
So, that's a whirlwind intro to implementing lazy JITing support for a new
architecture in Orc. I'll try to answer any questions you have on the
topic, though I'm not familiar with PowerPC at all. If you're comfortable
with PowerPC assembly I think it should be possible to implement once you
grok the concepts.
Hope this helps!
Cheers,
Lang.
On Jul 26, 2015, at 11:17 PM, Revital1 Eres <ERES at il.ibm.com> wrote:
Hi Again,
I'm a little confused regarding what is the exact Orc's functions I should
use
in order to save the functions code in a code cache so it could be later
replaced with different versions of it and I appreciate your help.
Just a reminder I want to dynamically recompile the program based on
profile
collected at the run-time. I would like to start executing the program
from
the code-cache and at some point be able to replace a function body with
it's
new compiled version; this can be done by replacing the entry in the
function
code with a trampoline to It's new version so that future calls to it
will
call the new version code.
Does the CompileOnDemandLayer executes the program from a code cache
and holds pointers to the code of the functions it executes? I am
compiling for Power machine.
Is there a target specific pieces that I should implement for making Orc
work on Power?
Thanks again,
Revital
From: Lang Hames <lhames at gmail.com>
To: Revital1 Eres/Haifa/IBM at IBMIL
Cc: LLVM Developers Mailing List <llvmdev at cs.uiuc.edu>
Date: 20/07/2015 08:41 PM
Subject: Re: [LLVMdev] Help with using LLVM to re-compile hot
functions at run-time
Hi Revital,
The CompileOnDemand layer is used by the lazy bitcode JIT in the lli tool.
You can find the code in llvm/tools/lli/OrcLazyJIT.* .
Cheers,
Lang.
On Mon, Jul 20, 2015 at 2:32 AM, Revital1 Eres <ERES at il.ibm.com> wrote:
Hello Lang,
Thanks for your answer.
I am now looking for an example of the usage of CompileOnDemandLayer. Is
there an example available for that (could not find one in llvm/examples)?
Thanks,
Revital
From: Lang Hames <lhames at gmail.com>
To: Revital1 Eres/Haifa/IBM at IBMIL
Cc: LLVM Developers Mailing List <llvmdev at cs.uiuc.edu>
Date: 10/07/2015 12:10 AM
Subject: Re: [LLVMdev] Help with using LLVM to re-compile hot
functions at run-time
Hi Revital,
LLVM does have an IR interpreter, but I don't think it's maintained well
(or possibly at all). The interpreter is also not designed to interact
with the LLVM JITs.
We generally encourage people to just JIT LLVM IR, rather than
interpreting it. For the use-case you have described, you could JIT IR
with no optimizations to begin with, then re-JIT hot functions at a higher
level.
The Orc JIT APIs (LLVM's newer JIT APIs) were written with this kind of
use-case in mind, and are probably a better fit for this than MCJIT. There
is no built-in hot-function detection or recompilation yet, but I think
this would be *fairly* easy to write in terms of Orc's callback API.
Cheers,
Lang.
On Thu, Jul 9, 2015 at 4:19 AM, Revital1 Eres <ERES at il.ibm.com> wrote:
Hello,
I am new to LLVM and a I appreciate your help with the following:
I want to run the LLVM IR through virtual machine (LLVM interpreter?) and
jit
compile the hot functions (using MCJIT).
This task will require amongst other identifying the hot functions and
having a
code cache that should be patched with the native code of the functions
after
they are jitted.
I've read so far about MCJIT and lli however I have not seen that the LLVM
interpreter can be used as a VM the way I was looking for; meaning
execute the code one instruction at a time; have a profiling mode to
identify hot functions and call jit to compile the hot functions.
I appreciate any advice/starting points for this project.
Thanks,
Revital
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