Use tagged CodeInstances for AbstractInterpreter caching #52233

vchuravy · 2023-11-19T23:13:37Z

Currently external AbstractInterpreters all follow the pattern
that CACHE = IdDict{MethodInstance,CodeInstance}. The NativeInterpreter
has the benefit that each MethodInstance carries an inline cache of CodeInstances.

CodeInstances pull triple duty, they contain validity information (min_world, max_world),
the inference state cache and the compilation state cache.

When we currently create a CodeInstance we don't record the owner and we thus construct detached CodeInstances.

In this PR I introduce the notion of tagging the code instances with the owner (nothing meaning native),
thus allowing foreign code instances to be stored in the inline cache.

GPUCompiler/CUDA would change it's caching strategy from IdDict{MethodInstance, CodeInstance} to IdDict{CodeInstance, LLVM.Module}
or similar. Ideally we would allow polymorphism for the compilation state part of the code instance, but that seems to invasive for now.

This has the benefit that CodeInstances are handled by caching and it would allow us to cache inference results
from foreign abstract interpreters across sessions.

The downside is that the cache walk now is a bit slower since we need to filter on owner. If this turns out to be
a large bottleneck we could bifurcate the cache on owner.

TODO:

~~Replace the params->lookup(mi, world, world) with a jl_rettype_inferred(owner, mi, world, world)~~ Defered to follow-up
Adapt AbstractInterpreter tests
Adapt out-of-tree abstract interpreters
- Use InternalCodeCache JuliaGPU/GPUCompiler.jl#534
- Support tagged CodeInstance JuliaDebug/Cthulhu.jl#520
Write a test that demonstrates across session caching.

Unresolved

What to do about epheremal users like REPLInterpreter, should those go into mi.cache
- Same question for applies to Cthulhu. I would prefer not having to support the old caching style (since it won't get backedge updates)
Uses of jl_rettype_inferred_native, which ones should receive a owner token.

Keno · 2023-11-20T13:30:39Z

I think this is fine, but I do wonder whether this is slightly premature. Just to clarify, the primary motivation here is not the performance of the IdDict implementation, but cache maintenance on world age invalidation? That seems like a good enough reason to me. My primary concern is that I'm not sure whether we may need to invalidate other things as part of the CodeInstance also. This kind of change just feels like the kind of thing you do once everything else is figured out.

vchuravy · 2023-11-20T14:09:58Z

but cache maintenance on world age invalidation? That seems like a good enough reason to me.

This is motivated by what GPUCompiler need today, We have a sever latency issue for GPU based codes that is prohibitive for both HPC and application deployment.
The primary source of the latency is cross-session inference caches, and while we spend quite some time looking at building alternatives in the GPUCompiler stack,
re-using the base infrastructure seems to be the most straightforward, we do need to be careful that this information isn't resused by the wrong abstract interpreter,
so tagging the CodeInstance for validation purposes would have been an independent sensible change.

My primary concern is that I'm not sure whether we may need to invalidate other things as part of the CodeInstance

Yeah I would love some additional flexibility with what could be stored in a CodeInstance, but I am planning on doing forward validation for any information based on this.

Keno · 2023-11-20T14:30:15Z

Ok, I didn't quite get the serialization implications of this change. Regardless, as I said, I don't think there's anything particularly wrong with it. 234a758 went a similar direction with respect to external interpreter analyses.

vchuravy · 2023-11-21T19:12:08Z

src/staticdata.c

+        // if (ci !in ci->defs->cache)
+        //     record_field_change((jl_value_t**)&ci->next, NULL);
+        // Why are we checking that the method/module this orignates from is in_image?
+        // and then disconnect this CI?
        if (jl_object_in_image((jl_value_t*)ci->def->def.value)) {


@vtjnash @timholy do either of you remember why we have this additional condition here?

Sorry to be late to the party. It was added in #48751 so @vtjnash is the expert, but I interpret this as a way to truncate traversal. The point is that if you've already cached the method you've brought in everything you should and nothing you shouldn't (e.g.,

julia/src/staticdata.c

Lines 791 to 799 in a28e553

else if (jl_is_method(def) && jl_object_in_image(def)) {

// we only need 3 specific fields of this (the rest are restored afterward, if valid)

// in particular, cache is repopulated by jl_mi_cache_insert for all foreign function,

// so must not be present here

record_field_change((jl_value_t**)&mi->uninferred, NULL);

record_field_change((jl_value_t**)&mi->backedges, NULL);

record_field_change((jl_value_t**)&mi->callbacks, NULL);

record_field_change((jl_value_t**)&mi->cache, NULL);

}

).

vchuravy · 2023-11-23T02:07:08Z

@aviatesk I think this is ready for a first review.

vchuravy · 2023-11-23T02:09:24Z

test/compiler/EscapeAnalysis/EAUtils.jl

@@ -86,7 +83,7 @@ struct EscapeCacheInfo
 end

 struct EscapeCache
-    cache::IdDict{MethodInstance,EscapeCacheInfo}
+    cache::IdDict{MethodInstance,EscapeCacheInfo} # Should this be CodeInstance to EscapeCacheInfo?


@aviatesk this is something we should talk about. In my head this should probably be an IdDict{CodeInstance, EscapeCacheInfo} since we are attaching information to a particular inference task and we store that information in the CodeInstance

Yeah, I agree. I would like to work on that refactoring to see what possibilities this change opens up, if you want.

That would be great!

base/compiler/cicache.jl

stdlib/REPL/src/REPLCompletions.jl

vchuravy · 2023-11-24T20:20:53Z

test/compiler/invalidation.jl

-@test any(INVALIDATION_TESTER_CACHE.dict) do (mi, ci)
-    mi.def.name === :basic_caller
+
+let mi = only(Base.specializations(only(methods(basic_caller))))


We can make this logic simpler after #52176

base/compiler/cicache.jl

vchuravy · 2023-11-26T00:38:59Z

@nanosoldier runtests(configuration = (buildflags=["LLVM_ASSERTIONS=1", "FORCE_ASSERTIONS=1"],), vs_configuration = (buildflags = ["LLVM_ASSERTIONS=1", "FORCE_ASSERTIONS=1"],))

base/compiler/cicache.jl

nanosoldier · 2023-11-26T10:19:34Z

The package evaluation job you requested has completed - possible new issues were detected.
The full report is available.

vchuravy · 2023-11-27T20:09:04Z

Mostly just needed API changes, but Krotov is worth a closer look.

BoundsError(a=Array{Any, 1}(dims=(207,), mem=Memory{Any}(207, 0x7f53d847dc60)[SSAValue(1), SSAValue(2), SSAValue(3), SSAValue(4), nothing, SSAValue(5), SSAValue(6), SSAValue(7), SSAValue(8), SSAValue(9), SSAValue(10), SSAValue(11), SSAValue(12), SSAValue(13), SSAValue(14), SSAValue(15), SSAValue(16), SSAValue(17), SSAValue(18), SSAValue(19), SSAValue(20), SSAValue(21), SSAValue(22), SSAValue(23), SSAValue(24), SSAValue(25), SSAValue(26), SSAValue(27), SSAValue(28), SSAValue(29), SSAValue(30), SSAValue(31), SSAValue(32), SSAValue(33), SSAValue(34), SSAValue(35), SSAValue(36), SSAValue(37), SSAValue(38), SSAValue(39), SSAValue(40), SSAValue(41), SSAValue(42), SSAValue(43), SSAValue(44), SSAValue(45), SSAValue(46), SSAValue(47), SSAValue(48), SSAValue(49), SSAValue(50), SSAValue(51), SSAValue(52), SSAValue(53), SSAValue(54), SSAValue(55), nothing, SSAValue(56), SSAValue(57), SSAValue(58), SSAValue(59), nothing, SSAValue(61), SSAValue(62), SSAValue(63), SSAValue(64), SSAValue(65), SSAValue(66), SSAValue(67), SSAValue(68), SSAValue(69), SSAValue(70), SSAValue(71), SSAValue(72), SSAValue(73), SSAValue(74), SSAValue(75), SSAValue(76), SSAValue(77), SSAValue(78), SSAValue(79), SSAValue(80), SSAValue(81), SSAValue(82), SSAValue(83), SSAValue(84), SSAValue(85), SSAValue(86), SSAValue(87), SSAValue(88), SSAValue(89), SSAValue(90), SSAValue(91), SSAValue(92), SSAValue(93), SSAValue(94), SSAValue(95), SSAValue(96), SSAValue(97), SSAValue(98), SSAValue(99), SSAValue(100), SSAValue(101), SSAValue(102), SSAValue(103), SSAValue(104), SSAValue(105), SSAValue(106), SSAValue(107), SSAValue(108), SSAValue(109), SSAValue(110), SSAValue(111), SSAValue(112), SSAValue(113), SSAValue(114), SSAValue(115), SSAValue(116), SSAValue(117), SSAValue(118), SSAValue(119), SSAValue(120), SSAValue(121), SSAValue(122), SSAValue(123), SSAValue(124), SSAValue(125), SSAValue(126), SSAValue(127), SSAValue(128), SSAValue(129), SSAValue(130), SSAValue(131), SSAValue(132), SSAValue(133), SSAValue(134), SSAValue(135), SSAValue(136), nothing, SSAValue(137), SSAValue(138), SSAValue(139), SSAValue(140), SSAValue(141), SSAValue(142), SSAValue(143), SSAValue(144), SSAValue(145), SSAValue(146), SSAValue(147), SSAValue(148), SSAValue(149), nothing, nothing, nothing, SSAValue(150), nothing, nothing, nothing, nothing, SSAValue(153), SSAValue(154), SSAValue(155), SSAValue(156), SSAValue(157), SSAValue(158), SSAValue(159), SSAValue(160), SSAValue(161), SSAValue(162), SSAValue(163), SSAValue(164), SSAValue(165), SSAValue(166), SSAValue(167), SSAValue(168), SSAValue(169), SSAValue(170), SSAValue(171), SSAValue(172), SSAValue(173), SSAValue(174), SSAValue(175), SSAValue(176), SSAValue(177), SSAValue(178), SSAValue(179), SSAValue(180), SSAValue(181), SSAValue(182), SSAValue(183), SSAValue(184), SSAValue(185), SSAValue(186), SSAValue(187), SSAValue(188), SSAValue(189), SSAValue(190), SSAValue(191), SSAValue(192), SSAValue(193), SSAValue(194), SSAValue(195), SSAValue(196), SSAValue(197), SSAValue(198), SSAValue(199)]), i=(256,))
throw_boundserror at ./essentials.jl:14
getindex at ./essentials.jl:811 [inlined]
fixup_node at ./compiler/ssair/ir.jl:1819
fixup_phinode_values! at ./compiler/ssair/ir.jl:1796
fixup_node at ./compiler/ssair/ir.jl:1805
just_fixup! at ./compiler/ssair/ir.jl:1853
just_fixup! at ./compiler/ssair/ir.jl:1843 [inlined]
non_dce_finish! at ./compiler/ssair/ir.jl:1893 [inlined]
finish at ./compiler/ssair/ir.jl:1902 [inlined]
compact! at ./compiler/ssair/ir.jl:1933
run_passes_ipo_safe at ./compiler/optimize.jl:903
run_passes_ipo_safe at ./compiler/optimize.jl:918 [inlined]
optimize at ./compiler/optimize.jl:892
jfptr_optimize_44501.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:2881 [inlined]
ijl_apply_generic at /source/src/gf.c:3063
_typeinf at ./compiler/typeinfer.jl:264
typeinf at ./compiler/typeinfer.jl:216
typeinf_ext at ./compiler/typeinfer.jl:1040
typeinf_ext_toplevel at ./compiler/typeinfer.jl:1074
typeinf_ext_toplevel at ./compiler/typeinfer.jl:1070

But this may be unrelated to this PR.

base/compiler/cicache.jl

aviatesk

I generally think it's good, particularly the way it simplifies the external AbstractInterpreter's code cache. On the other hand, as Keno pointed out, I'm not completely clear on the serialization support. Am I right in thinking that this PR itself enables the serialization of CodeInstance inferred by an external AbstractInterpreter?

aviatesk · 2023-12-08T04:09:52Z

src/gf.c

@@ -315,7 +315,7 @@ jl_datatype_t *jl_mk_builtin_func(jl_datatype_t *dt, const char *name, jl_fptr_a
    jl_atomic_store_relaxed(&m->unspecialized, mi);
    jl_gc_wb(m, mi);

-    jl_code_instance_t *codeinst = jl_new_codeinst(mi,
+    jl_code_instance_t *codeinst = jl_new_codeinst(mi, jl_nothing,


Maybe define

JL_DLLEXPORT jl_code_instance_t *jl_new_codeinst_native( jl_method_instance_t *mi, jl_value_t *rettype, jl_value_t *exctype, jl_value_t *inferred_const, jl_value_t *inferred, int32_t const_flags, size_t min_world, size_t max_world, uint32_t ipo_effects, uint32_t effects, jl_value_t *analysis_results, uint8_t relocatability /*, jl_array_t *edges, int absolute_max*/) { return jl_new_codeinst(mi, /*owner*/jl_nothing, rettype, exctype, inferred_const, inferred, const_flags, min_world, max_world, ipo_effects, effects, analysis_results, relocatability /*, edges, absolute_max*/); }

and make it more explicit where we have native compilation specific code?

The next step would be to create a field in jl_task_t and use that to propagate the compilation context, which will remove the _native function again.

Implementing it with #50958 e.g. as a reference seems feasible. If that's the case, it might be best to keep the current code unchanged.

src/gf.c

stdlib/REPL/src/REPLCompletions.jl

test/compiler/newinterp.jl

aviatesk · 2023-12-08T04:58:44Z

src/gf.c

-// call external callbacks registered with this method_instance
-static void invalidate_external(jl_method_instance_t *mi, size_t max_world) {


It's nice we no longer need this since agged CodeInstance automatically gains support for invalidation -- CodeInstance inferred by each AbstractInterpreter is appended to the next linked list, and they are invalidated by manipulating max_world, irrespective of their owner.

aviatesk · 2023-12-08T05:08:13Z

test/compiler/AbstractInterpreter.jl

@@ -442,7 +442,8 @@ function custom_lookup(mi::MethodInstance, min_world::UInt, max_world::UInt)
            end
        end
    end
-    return CONST_INVOKE_INTERP.code_cache.dict[mi]
+    # XXX: This seems buggy, custom_lookup should probably construct the absint on demand.


It's hacky. We need a way to set a contextual AbstractInterpreter globally.

As far as I understand it AbstractInterpreters are ephemeral. Since they capture the world they operate in on construction.

aviatesk · 2023-12-08T05:12:24Z

test/compiler/EscapeAnalysis/EAUtils.jl

@@ -86,7 +83,7 @@ struct EscapeCacheInfo
 end

 struct EscapeCache
-    cache::IdDict{MethodInstance,EscapeCacheInfo}
+    cache::IdDict{MethodInstance,EscapeCacheInfo} # Should this be CodeInstance to EscapeCacheInfo?


Yeah, I agree. I would like to work on that refactoring to see what possibilities this change opens up, if you want.

test/compiler/invalidation.jl

For external abstract interpreters like JET, which propagate custom data interprocedurally, it is essential to inject custom behaviors into where cached regular/constant inference results are used. Previously, this was accomplished by overloading both `abstract_call_method` and `get(::WorldView{CustomView}, ...)` (and `const_prop_call` and `cached_lookup`), that method was admittedly hacky and should probably better to be avoided. Moreover, after #52233, doing so has become infeasible when the external abstract interpreter uses `InternalCodeCache`. To address this issue, this commit provides an interface named `return_cached_result`. This allows external abstract interpreters to inject custom interprocedural data propagation during abstract interpretation even when they use `InternalCodeCache`.

Leverages JuliaLang/julia#52233 to use the internal code cache that comes with the inherent invalidation support. Still requires: - JuliaLang/julia#53300 (or JuliaLang/julia#53219) - JuliaLang/julia#53318

This lacks invalidation support (since this commit still uses the external code cache), but this lets JET to run on the latest nightly at least.

Leverages JuliaLang/julia#52233 to use the internal code cache that comes with the inherent invalidation support. Still requires: - JuliaLang/julia#53300 (or JuliaLang/julia#53219) - JuliaLang/julia#53318

It has been possible for external abstract interpreters to keep custom data in `codeinst.inferred` (together /w overloading `inlining_policy`). After JuliaLang#52233, when such external absint uses `InternalCodeCache`, this data is passed to `jl_ir_flag_inferred`, leading to segfaults in assertion builds. This commit resolves the issue by omitting `jl_ir_flag_inferred` checks when the `cache_owner` is external. Nonetheless, a better resolution might be necessary. It suggests that the current design of `code_owner` and `InternalCodeCache` for the external cache system is somewhat flawed. A conceivable approach could involve: - Adding a layer similar to `inlining_policy` in `CC.get(::WorldView{InternalCodeCache})` to enable safe redirection of custom data to the native interpreter's implementation. - Prohibiting custom data in the `inferred` field and directing such data to be kept in `analysis_results`.

For external abstract interpreters like JET, which propagate custom data interprocedurally, it is essential to inject custom behaviors into where cached regular/constant inference results are used. Previously, this was accomplished by overloading both `abstract_call_method` and `get(::WorldView{CustomView}, ...)` (and `const_prop_call` and `cached_lookup`), that method was admittedly hacky and should probably better to be avoided. Moreover, after JuliaLang#52233, doing so has become infeasible when the external abstract interpreter uses `InternalCodeCache`. To address this issue, this commit provides an interface named `return_cached_result`. This allows external abstract interpreters to inject custom interprocedural data propagation during abstract interpretation even when they use `InternalCodeCache`.

Leverages JuliaLang/julia#52233 to use the internal code cache that comes with the inherent invalidation support. Still requires: - JuliaLang/julia#53300 (or JuliaLang/julia#53219) - JuliaLang/julia#53318

#53318) For external abstract interpreters like JET, which propagate custom data interprocedurally, it is essential to inject custom behaviors into where cached regular/constant inference results are used. Previously, this was accomplished by overloading both `abstract_call_method` and `get(::WorldView{CustomView}, ...)` (and `const_prop_call` and `cached_lookup`), that method was admittedly hacky and should probably better to be avoided. Moreover, after #52233, doing so has become infeasible when the external abstract interpreter uses `InternalCodeCache`. To address this issue, this commit provides an interface named `return_cached_result`. This allows external abstract interpreters to inject custom interprocedural data propagation during abstract interpretation even when they use `InternalCodeCache`.

Two small cleanups to #52233 - Don't use foreign code-instances for native code caching decision making - don't return a non-native codeinst for jl_method_compiled --------- Co-authored-by: Keno Fischer <keno@juliahub.com>

It has been possible for external abstract interpreters to keep custom data in `codeinst.inferred` (together /w overloading `inlining_policy`). After #52233, when such external absint uses `InternalCodeCache`, this data is passed to `jl_ir_flag_inferred`, leading to segfaults in assertion builds. This commit resolves the issue by omitting `jl_ir_flag_inferred` checks when the `cache_owner` is external. Nonetheless, a better resolution might be necessary. It suggests that the current design of `code_owner` and `InternalCodeCache` for the external cache system is somewhat flawed. A conceivable approach could involve: - Adding a layer similar to `inlining_policy` in `CC.get(::WorldView{InternalCodeCache})` to enable safe redirection of custom data to the native interpreter's implementation. - Prohibiting custom data in the `inferred` field and directing such data to be kept in `analysis_results`.

) It has been possible for external abstract interpreters to keep custom data in `codeinst.inferred` (together /w overloading `inlining_policy`). After #52233, when such external absint uses `InternalCodeCache`, this data is passed to `jl_ir_flag_inferred`, leading to segfaults in assertion builds. This commit resolves the issue by omitting `jl_ir_flag_inferred` checks when the `cache_owner` is external. Nonetheless, a better resolution might be necessary. It suggests that the current design of `code_owner` and `InternalCodeCache` for the external cache system is somewhat flawed. A conceivable approach could involve: - Adding a layer similar to `inlining_policy` in `CC.get(::WorldView{InternalCodeCache})` to enable safe redirection of custom data to the native interpreter's implementation. - Prohibiting custom data in the `inferred` field and directing such data to be kept in `analysis_results`.

) It has been possible for external abstract interpreters to keep custom data in `codeinst.inferred` (together /w overloading `inlining_policy`). After #52233, when such external absint uses `InternalCodeCache`, this data is passed to `jl_ir_flag_inferred`, leading to segfaults in assertion builds. This commit resolves the issue by omitting `jl_ir_flag_inferred` checks when the `cache_owner` is external. Nonetheless, a better resolution might be necessary. It suggests that the current design of `code_owner` and `InternalCodeCache` for the external cache system is somewhat flawed. A conceivable approach could involve: - Adding a layer similar to `inlining_policy` in `CC.get(::WorldView{InternalCodeCache})` to enable safe redirection of custom data to the native interpreter's implementation. - Prohibiting custom data in the `inferred` field and directing such data to be kept in `analysis_results`. (cherry picked from commit 93876c9)

Two small cleanups to JuliaLang#52233 - Don't use foreign code-instances for native code caching decision making - don't return a non-native codeinst for jl_method_compiled --------- Co-authored-by: Keno Fischer <keno@juliahub.com>

…iaLang#53300) It has been possible for external abstract interpreters to keep custom data in `codeinst.inferred` (together /w overloading `inlining_policy`). After JuliaLang#52233, when such external absint uses `InternalCodeCache`, this data is passed to `jl_ir_flag_inferred`, leading to segfaults in assertion builds. This commit resolves the issue by omitting `jl_ir_flag_inferred` checks when the `cache_owner` is external. Nonetheless, a better resolution might be necessary. It suggests that the current design of `code_owner` and `InternalCodeCache` for the external cache system is somewhat flawed. A conceivable approach could involve: - Adding a layer similar to `inlining_policy` in `CC.get(::WorldView{InternalCodeCache})` to enable safe redirection of custom data to the native interpreter's implementation. - Prohibiting custom data in the `inferred` field and directing such data to be kept in `analysis_results`.

@rayegun

For GPUCompiler we would like to support a native on disk cache of LLVM IR. One of the longstanding issues has been the cache invalidation of such an on disk cache. With #52233 we now have an integrated cache for the inference results and we can rely on `CodeInstance` to be stable across sessions. Due to #52119 we can also rely on the `objectid` to be stable. My inital thought was to key the native disk cache in GPUCompiler on the objectid of the corresponding CodeInstance (+ some compilation parameters). While discussing this with @rayegun yesterday we noted that having a CodeInstance with the same objectid might not be enough provenance. E.g we are not gurantueed that the CodeInstance is from the same build artifact and the same precise source code. For the package images we are tracking this during loading and validate all contents at once, and we keep explicitly track of the provenance chain. This PR adds a lookup up table where we map from "external_blobs" e.g. loaded images, to the corresponding top module of each image, and uses this to determine the build_id of the package image.

…reters (#54069) Partially reverts #49391 PrecompileTools uses the timing infrastructure to snoop on the inference process. The reason for #49391 was that this could lead to accidental pollution of the caches with foreign results (timholy/SnoopCompile.jl#338) After #52233 and especially #53336 we now filter results by cache owner and don't try to cache foreign code using the native pipeline. Motivated by JuliaGPU/GPUCompiler.jl#567 which demonstrated that a foreign code instance would not be cached without PrecompileTools.

…reters (#54069) Partially reverts #49391 PrecompileTools uses the timing infrastructure to snoop on the inference process. The reason for #49391 was that this could lead to accidental pollution of the caches with foreign results (timholy/SnoopCompile.jl#338) After #52233 and especially #53336 we now filter results by cache owner and don't try to cache foreign code using the native pipeline. Motivated by JuliaGPU/GPUCompiler.jl#567 which demonstrated that a foreign code instance would not be cached without PrecompileTools. (cherry picked from commit c0611e8)

@rayegun

For GPUCompiler we would like to support a native on disk cache of LLVM IR. One of the longstanding issues has been the cache invalidation of such an on disk cache. With #52233 we now have an integrated cache for the inference results and we can rely on `CodeInstance` to be stable across sessions. Due to #52119 we can also rely on the `objectid` to be stable. My inital thought was to key the native disk cache in GPUCompiler on the objectid of the corresponding CodeInstance (+ some compilation parameters). While discussing this with @rayegun yesterday we noted that having a CodeInstance with the same objectid might not be enough provenance. E.g we are not gurantueed that the CodeInstance is from the same build artifact and the same precise source code. For the package images we are tracking this during loading and validate all contents at once, and we keep explicitly track of the provenance chain. This PR adds a lookup up table where we map from "external_blobs" e.g. loaded images, to the corresponding top module of each image, and uses this to determine the build_id of the package image. (cherry picked from commit d47cbf6)

vchuravy added speculative Whether the change will be implemented is speculative compiler:inference Type inference caching labels Nov 19, 2023

vchuravy requested review from aviatesk and maleadt November 19, 2023 23:13

vchuravy force-pushed the vc/tagged_ci branch from 1990bfb to 6a5c024 Compare November 20, 2023 01:35

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Use InternalCodeCache JuliaGPU/GPUCompiler.jl#534

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Support tagged CodeInstance JuliaDebug/Cthulhu.jl#520

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Investigate if we need a custom hash for EnzymeCompilerParams EnzymeAD/Enzyme.jl#1182

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AbsInt: add interfaces to customize cases when cached results are used #53318

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switch to using the internal code cache aviatesk/JET.jl#611

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aviatesk added a commit to aviatesk/JET.jl that referenced this pull request Feb 13, 2024

add minimum adjustments to JuliaLang/julia#52233

98c47ac

This lacks invalidation support (since this commit still uses the external code cache), but this lets JET to run on the latest nightly at least.

aviatesk added a commit to aviatesk/JET.jl that referenced this pull request Feb 13, 2024

add minimum adjustments to JuliaLang/julia#52233

09905ef

This lacks invalidation support (since this commit still uses the external code cache), but this lets JET to run on the latest nightly at least.

vchuravy mentioned this pull request Feb 14, 2024

Cleanups for tagged code instance #53336

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aviatesk mentioned this pull request Feb 27, 2024

Track issues with external abstract interpreter from the recent CodeInstance refactors #53498

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This was referenced Apr 3, 2024

Allow for querying of build_id from objects #53943

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Add disk cache infrastructure for Julia 1.11 JuliaGPU/GPUCompiler.jl#557

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vchuravy mentioned this pull request Apr 13, 2024

Allow PrecompileTools to see MI's inferred by foreign abstract interpreters #54069

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Use tagged CodeInstances for AbstractInterpreter caching #52233

Use tagged CodeInstances for AbstractInterpreter caching #52233

vchuravy commented Nov 19, 2023 •

edited

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Keno commented Nov 20, 2023

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	else if (jl_is_method(def) && jl_object_in_image(def)) {
	// we only need 3 specific fields of this (the rest are restored afterward, if valid)
	// in particular, cache is repopulated by jl_mi_cache_insert for all foreign function,
	// so must not be present here
	record_field_change((jl_value_t**)&mi->uninferred, NULL);
	record_field_change((jl_value_t**)&mi->backedges, NULL);
	record_field_change((jl_value_t**)&mi->callbacks, NULL);
	record_field_change((jl_value_t**)&mi->cache, NULL);
	}

		// call external callbacks registered with this method_instance
		static void invalidate_external(jl_method_instance_t *mi, size_t max_world) {

Use tagged CodeInstances for AbstractInterpreter caching #52233

Use tagged CodeInstances for AbstractInterpreter caching #52233

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vchuravy commented Nov 19, 2023 • edited Loading

TODO:

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vchuravy commented Nov 19, 2023 •

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