This class is turning into a useful interface, rather than an implementation
detail, so I'm dropping the 'Base' suffix.
No functional change.
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memory, rather than representing the stubs in IR. Update the CompileOnDemand
layer to use this functionality.
Directly emitting stubs is much cheaper than building them in IR and codegen'ing
them (see below). It also plays well with remote JITing - stubs can be emitted
directly in the target process, rather than having to send them over the wire.
The downsides are:
(1) Care must be taken when resolving symbols, as stub symbols are held in a
separate symbol table. This is only a problem for layer writers and other
people using this API directly. The CompileOnDemand layer hides this detail.
(2) Aliases of function stubs can't be symbolic any more (since there's no
symbol definition in IR), but must be converted into a constant pointer
expression. This means that modules containing aliases of stubs cannot be
cached. In practice this is unlikely to be a problem: There's no benefit to
caching such a module anyway.
On balance I think the extra performance is more than worth the trade-offs: In a
simple stress test with 10000 dummy functions requiring stubs and a single
executed "hello world" main function, directly emitting stubs reduced user time
for JITing / executing by over 90% (1.5s for IR stubs vs 0.1s for direct
emission).
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This allows modules containing aliases to be lazily jit'd. Previously these
failed with missing symbol errors because the aliases weren't cloned from the
original module.
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into partitions. Also, add an option to clone stub definitions (not just decls)
into partitions: these definitions could be inlined in some places to avoid the
overhead of calling via the stub.
Found by inspection - no test case yet, although I plan to add a unit test for
this once the CompileOnDemand layer refactoring settles down.
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and avoid cloning unused decls into every partition.
Module partitioning showed up as a source of significant overhead when I
profiled some trivial test cases. Avoiding the overhead of partitionging
for uncalled functions helps to mitigate this.
This change also means that it is no longer necessary to have a
LazyEmittingLayer underneath the CompileOnDemand layer, since the
CompileOnDemandLayer will not extract or emit function bodies until they are
called.
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the function body.
This is necessary for correctness when lazily compiling.
Also, flesh out the Orc unit test infrastructure slightly, and add a unit test
for this.
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This patch replaces most of the Orc indirection utils API with a new class:
JITCompileCallbackManager, which creates and manages JIT callbacks.
Exposing this functionality directly allows the user to create callbacks that
are associated with user supplied compilation actions. For example, you can
create a callback to lazyily IR-gen something from an AST. (A kaleidoscope
example demonstrating this will be committed shortly).
This patch also refactors the CompileOnDemand layer to use the
JITCompileCallbackManager API.
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This patch adds a new set of JIT APIs to LLVM. The aim of these new APIs is to
cleanly support a wider range of JIT use cases in LLVM, and encourage the
development and contribution of re-usable infrastructure for LLVM JIT use-cases.
These APIs are intended to live alongside the MCJIT APIs, and should not affect
existing clients.
Included in this patch:
1) New headers in include/llvm/ExecutionEngine/Orc that provide a set of
components for building JIT infrastructure.
Implementation code for these headers lives in lib/ExecutionEngine/Orc.
2) A prototype re-implementation of MCJIT (OrcMCJITReplacement) built out of the
new components.
3) Minor changes to RTDyldMemoryManager needed to support the new components.
These changes should not impact existing clients.
4) A new flag for lli, -use-orcmcjit, which will cause lli to use the
OrcMCJITReplacement class as its underlying execution engine, rather than
MCJIT itself.
Tests to follow shortly.
Special thanks to Michael Ilseman, Pete Cooper, David Blaikie, Eric Christopher,
Justin Bogner, and Jim Grosbach for extensive feedback and discussion.
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