This PR changes the current JIT model from trace projection to trace recording. Benchmarking: better pyperformance (about 1.7% overall) geomean versus current https://raw.githubusercontent.com/facebookexperimental/free-threading-benchmarking/refs/heads/main/results/bm-20251108-3.15.0a1%2B-7e2bc1d-JIT/bm-20251108-vultr-x86_64-Fidget%252dSpinner-tracing_jit-3.15.0a1%2B-7e2bc1d-vs-base.svg, 100% faster Richards on the most improved benchmark versus the current JIT. Slowdown of about 10-15% on the worst benchmark versus the current JIT. **Note: the fastest version isn't the one merged, as it relies on fixing bugs in the specializing interpreter, which is left to another PR**. The speedup in the merged version is about 1.1%. https://raw.githubusercontent.com/facebookexperimental/free-threading-benchmarking/refs/heads/main/results/bm-20251112-3.15.0a1%2B-f8a764a-JIT/bm-20251112-vultr-x86_64-Fidget%252dSpinner-tracing_jit-3.15.0a1%2B-f8a764a-vs-base.svg Stats: 50% more uops executed, 30% more traces entered the last time we ran them. It also suggests our trace lengths for a real trace recording JIT are too short, as a lot of trace too long aborts https://github.com/facebookexperimental/free-threading-benchmarking/blob/main/results/bm-20251023-3.15.0a1%2B-eb73378-CLANG%2CJIT/bm-20251023-vultr-x86_64-Fidget%252dSpinner-tracing_jit-3.15.0a1%2B-eb73378-pystats-vs-base.md . This new JIT frontend is already able to record/execute significantly more instructions than the previous JIT frontend. In this PR, we are now able to record through custom dunders, simple object creation, generators, etc. None of these were done by the old JIT frontend. Some custom dunders uops were discovered to be broken as part of this work gh-140277 The optimizer stack space check is disabled, as it's no longer valid to deal with underflow. Pros: * Ignoring the generated tracer code as it's automatically created, this is only additional 1k lines of code. The maintenance burden is handled by the DSL and code generator. * `optimizer.c` is now significantly simpler, as we don't have to do strange things to recover the bytecode from a trace. * The new JIT frontend is able to handle a lot more control-flow than the old one. * Tracing is very low overhead. We use the tail calling interpreter/computed goto interpreter to switch between tracing mode and non-tracing mode. I call this mechanism dual dispatch, as we have two dispatch tables dispatching to each other. Specialization is still enabled while tracing. * Better handling of polymorphism. We leverage the specializing interpreter for this. Cons: * (For now) requires tail calling interpreter or computed gotos. This means no Windows JIT for now :(. Not to fret, tail calling is coming soon to Windows though https://github.com/python/cpython/pull/139962 Design: * After each instruction, the `record_previous_inst` function/label is executed. This does as the name suggests. * The tracing interpreter lowers bytecode to uops directly so that it can obtain "fresh" values at the point of lowering. * The tracing version behaves nearly identical to the normal interpreter, in fact it even has specialization! This allows it to run without much of a slowdown when tracing. The actual cost of tracing is only a function call and writes to memory. * The tracing interpreter uses the specializing interpreter's deopt to naturally form the side exit chains. This allows it to side exit chain effectively, without repeating much code. We force a re-specializing when tracing a deopt. * The tracing interpreter can even handle goto errors/exceptions, but I chose to disable them for now as it's not tested. * Because we do not share interpreter dispatch, there is should be no significant slowdown to the original specializing interpreter on tailcall and computed got with JIT disabled. With JIT enabled, there might be a slowdown in the form of the JIT trying to trace. * Things that could have dynamic instruction pointer effects are guarded on. The guard deopts to a new instruction --- `_DYNAMIC_EXIT`.
117 lines
3.8 KiB
Python
117 lines
3.8 KiB
Python
"""Generate targets for computed goto dispatch
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Reads the instruction definitions from bytecodes.c.
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Writes the table to opcode_targets.h by default.
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"""
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import argparse
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from analyzer import (
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Analysis,
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analyze_files,
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)
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from generators_common import (
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DEFAULT_INPUT,
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ROOT,
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)
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from tier1_generator import UNKNOWN_OPCODE_HANDLER
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from cwriter import CWriter
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DEFAULT_OUTPUT = ROOT / "Python/opcode_targets.h"
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def write_opcode_targets(analysis: Analysis, out: CWriter) -> None:
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"""Write header file that defines the jump target table"""
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targets = ["&&_unknown_opcode,\n"] * 256
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for name, op in analysis.opmap.items():
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if op < 256:
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targets[op] = f"&&TARGET_{name},\n"
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out.emit("#if !_Py_TAIL_CALL_INTERP\n")
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out.emit("static void *opcode_targets_table[256] = {\n")
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for target in targets:
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out.emit(target)
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out.emit("};\n")
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targets = ["&&_unknown_opcode,\n"] * 256
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for name, op in analysis.opmap.items():
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if op < 256:
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targets[op] = f"&&record_previous_inst,\n"
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out.emit("#if _Py_TIER2\n")
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out.emit("static void *opcode_tracing_targets_table[256] = {\n")
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for target in targets:
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out.emit(target)
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out.emit("};\n")
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out.emit(f"#endif\n")
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out.emit("#else /* _Py_TAIL_CALL_INTERP */\n")
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def function_proto(name: str) -> str:
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return f"Py_PRESERVE_NONE_CC static PyObject *_TAIL_CALL_{name}(TAIL_CALL_PARAMS)"
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def write_tailcall_dispatch_table(analysis: Analysis, out: CWriter) -> None:
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out.emit("static py_tail_call_funcptr instruction_funcptr_handler_table[256];\n")
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out.emit("\n")
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out.emit("static py_tail_call_funcptr instruction_funcptr_tracing_table[256];\n")
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out.emit("\n")
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# Emit function prototypes for labels.
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for name in analysis.labels:
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out.emit(f"{function_proto(name)};\n")
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out.emit("\n")
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# Emit function prototypes for opcode handlers.
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for name in sorted(analysis.instructions.keys()):
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out.emit(f"{function_proto(name)};\n")
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out.emit("\n")
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# Emit unknown opcode handler.
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out.emit(function_proto("UNKNOWN_OPCODE"))
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out.emit(" {\n")
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out.emit("int opcode = next_instr->op.code;\n")
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out.emit(UNKNOWN_OPCODE_HANDLER)
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out.emit("}\n")
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out.emit("\n")
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# Emit the dispatch table.
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out.emit("static py_tail_call_funcptr instruction_funcptr_handler_table[256] = {\n")
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for name in sorted(analysis.instructions.keys()):
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out.emit(f"[{name}] = _TAIL_CALL_{name},\n")
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named_values = analysis.opmap.values()
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for rest in range(256):
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if rest not in named_values:
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out.emit(f"[{rest}] = _TAIL_CALL_UNKNOWN_OPCODE,\n")
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out.emit("};\n")
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# Emit the tracing dispatch table.
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out.emit("static py_tail_call_funcptr instruction_funcptr_tracing_table[256] = {\n")
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for name in sorted(analysis.instructions.keys()):
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out.emit(f"[{name}] = _TAIL_CALL_record_previous_inst,\n")
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named_values = analysis.opmap.values()
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for rest in range(256):
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if rest not in named_values:
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out.emit(f"[{rest}] = _TAIL_CALL_UNKNOWN_OPCODE,\n")
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out.emit("};\n")
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outfile.write("#endif /* _Py_TAIL_CALL_INTERP */\n")
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arg_parser = argparse.ArgumentParser(
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description="Generate the file with dispatch targets.",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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)
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arg_parser.add_argument(
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"-o", "--output", type=str, help="Generated code", default=DEFAULT_OUTPUT
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)
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arg_parser.add_argument(
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"input", nargs=argparse.REMAINDER, help="Instruction definition file(s)"
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)
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if __name__ == "__main__":
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args = arg_parser.parse_args()
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if len(args.input) == 0:
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args.input.append(DEFAULT_INPUT)
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data = analyze_files(args.input)
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with open(args.output, "w") as outfile:
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out = CWriter(outfile, 0, False)
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write_opcode_targets(data, out)
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write_tailcall_dispatch_table(data, out)
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