diff --git a/InternalDocs/frames.md b/InternalDocs/frames.md index 34682adb1b422e..19b7c8a665425b 100644 --- a/InternalDocs/frames.md +++ b/InternalDocs/frames.md @@ -36,6 +36,20 @@ This seems to provide the best performance without excessive complexity. The specials have a fixed size, so the offset of the locals is know. The interpreter needs to hold two pointers, a frame pointer and a stack pointer. +### Fast locals and evaluation stack + +The frame contains a single array of object pointers, `localsplus`, +which contains both the fast locals and the stack. The top of the +stack, including the locals, is indicated by `stacktop`. +For example, in a function with three locals, if the stack contains +one value, `frame->stacktop == 4`. + +The interpreters share an implementation which uses the same memory +but caches the depth (as a pointer) in a C local, `stack_pointer`. +We aren't sure yet exactly how the JIT will implement the stack; +likely some of the values near the top of the stack will be held in registers. + + #### Alternative layout An alternative layout that was used for part of 3.11 alpha was: @@ -124,6 +138,8 @@ if the frame were to resume. After `frame.f_lineno` is set, `instr_ptr` points t the next instruction to be executed. During a call to a python function, `instr_ptr` points to the call instruction, because this is what we would expect to see in an exception traceback. +Dispatching on `instr_ptr` would be very inefficient, so in Tier 1 we cache the +upcoming value of `instr_ptr` in the C local `next_instr`. The `return_offset` field determines where a `RETURN` should go in the caller, relative to `instr_ptr`. It is only meaningful to the callee, so it needs to diff --git a/Python/tier2_engine.md b/Python/tier2_engine.md index 5ceda8e806045d..5974fd156dab1b 100644 --- a/Python/tier2_engine.md +++ b/Python/tier2_engine.md @@ -148,3 +148,13 @@ TO DO. The implementation will change soon, so there is no point in documenting it until then. + +# Tier 2 IR format + +The tier 2 IR (Internal Representation) format is also the basis for the Tier 2 interpreter (though the two formats may eventually differ). This format is also used as the input to the machine code generator (the JIT compiler). + +Tier 2 IR entries are all the same size; there is no equivalent to `EXTENDED_ARG` or trailing inline cache entries. Each instruction is a struct with the following fields (all integers of varying sizes): + +- **opcode**: Sometimes the same as a Tier 1 opcode, sometimes a separate micro opcode. Tier 2 opcodes are 9 bits (as opposed to Tier 1 opcodes, which fit in 8 bits). By convention, Tier 2 opcode names start with `_`. +- **oparg**: The argument. Usually the same as the Tier 1 oparg after expansion of `EXTENDED_ARG` prefixes. Up to 32 bits. +- **operand**: An additional argument, Typically the value of *one* cache item from the Tier 1 inline cache, up to 64 bits. diff --git a/Python/vm-state.md b/Python/vm-state.md index b3246557dbeea3..b9a2e120ebf06e 100644 --- a/Python/vm-state.md +++ b/Python/vm-state.md @@ -3,39 +3,22 @@ ## Definition of Tiers - **Tier 1** is the classic Python bytecode interpreter. - This includes the specializing adaptive interpreter described in [PEP 659](https://peps.python.org/pep-0659/) and introduced in Python 3.11. -- **Tier 2**, also known as the micro-instruction ("uop") interpreter, is a new interpreter with a different instruction format. - It will be introduced in Python 3.13, and also forms the basis for a JIT using copy-and-patch technology that is likely to be introduced at the same time (but, unlike the Tier 2 interpreter, hasn't landed in the main branch yet). + This includes the specializing [adaptive interpreter](../InternalDocs/adaptive.md). +- **Tier 2**, also known as the micro-instruction ("uop") interpreter, is a new execution engine. + It was introduced in Python 3.13, and also forms the basis for a JIT using copy-and-patch technology. See [Tier 2](tier2_engine.md) for more information. -# Frame state -Almost all interpreter state is nominally stored in the frame structure. -A pointer to the current frame is held in `frame`. It contains: -- **local variables** (a.k.a. "fast locals") -- **evaluation stack** (tacked onto the end of the locals) -- **stack top** (an integer giving the top of the evaluation stack) -- **instruction pointer** -- **code object**, which holds things like the array of instructions, lists of constants and names referenced by certain instructions, the exception handling table, and the table that translates instruction offsets to line numbers -- **return offset**, only relevant during calls, telling the interpreter where to return - -There are some other fields in the frame structure of less importance; notably frames are linked together in a singly-linked list via the `previous` pointer, pointing from callee to caller. -The frame also holds a pointer to the current function, globals, builtins, and the locals converted to dict (used to support the `locals()` built-in). - -## Fast locals and evaluation stack - -The frame contains a single array of object pointers, `localsplus`, which contains both the fast locals and the stack. -The top of the stack, including the locals, is indicated by `stacktop`. -For example, in a function with three locals, if the stack contains one value, `frame->stacktop == 4`. +# Thread state and interpreter state -The interpreters share an implementation which uses the same memory but caches the depth (as a pointer) in a C local, `stack_pointer`. -We aren't sure yet exactly how the JIT will implement the stack; likely some of the values near the top of the stack will be held in registers. +An important piece of VM state is the **thread state**, held in `tstate`. +The current frame pointer, `frame`, is always equal to `tstate->current_frame`. +The thread state also holds the exception state (`tstate->exc_info`) and the recursion counters (`tstate->c_recursion_remaining` and `tstate->py_recursion_remaining`). -## Instruction pointer +The thread state is also used to access the **interpreter state** (`tstate->interp`), which is important since the "eval breaker" flags are stored there (`tstate->interp->ceval.eval_breaker`, an "atomic" variable), as well as the "PEP 523 function" (`tstate->interp->eval_frame`). +The interpreter state also holds the optimizer state (`optimizer` and some counters). +Note that the eval breaker may be moved to the thread state soon as part of the multicore (PEP 703) work. -The canonical, in-memory, representation of the instruction pointer is `frame->instr_ptr`. -It always points to an instruction in the bytecode array of the frame's code object. -Dispatching on `frame->instr_ptr` would be very inefficient, so in Tier 1 we cache the upcoming value of `frame->instr_ptr` in the C local `next_instr`. ## Tier 2 @@ -47,7 +30,7 @@ The Tier 2 instruction pointer is strictly internal to the Tier 2 interpreter, s ## Unwinding -Unwinding uses exception tables to find the next point at which normal execution can occur, or fail if there are no exception handlers. +Unwinding uses exception tables to find the next point at which normal execution can occur, or fail if there are no exception handlers. For more information on what exception tables are, see [exception handling](exception_handling.md). During unwinding both the stack and the instruction pointer should be in their canonical, in-memory representation. ## Jumps in bytecode @@ -68,23 +51,3 @@ Patching exits should be fairly straightforward in the interpreter. It will be more complex in the JIT. (We might also consider deoptimizations as a separate jump type.) - -# Thread state and interpreter state - -Another important piece of VM state is the **thread state**, held in `tstate`. -The current frame pointer, `frame`, is always equal to `tstate->current_frame`. -The thread state also holds the exception state (`tstate->exc_info`) and the recursion counters (`tstate->c_recursion_remaining` and `tstate->py_recursion_remaining`). - -The thread state is also used to access the **interpreter state** (`tstate->interp`), which is important since the "eval breaker" flags are stored there (`tstate->interp->ceval.eval_breaker`, an "atomic" variable), as well as the "PEP 523 function" (`tstate->interp->eval_frame`). -The interpreter state also holds the optimizer state (`optimizer` and some counters). -Note that the eval breaker may be moved to the thread state soon as part of the multicore (PEP 703) work. - -# Tier 2 IR format - -The tier 2 IR (Internal Representation) format is also the basis for the Tier 2 interpreter (though the two formats may eventually differ). This format is also used as the input to the machine code generator (the JIT compiler). - -Tier 2 IR entries are all the same size; there is no equivalent to `EXTENDED_ARG` or trailing inline cache entries. Each instruction is a struct with the following fields (all integers of varying sizes): - -- **opcode**: Sometimes the same as a Tier 1 opcode, sometimes a separate micro opcode. Tier 2 opcodes are 9 bits (as opposed to Tier 1 opcodes, which fit in 8 bits). By convention, Tier 2 opcode names start with `_`. -- **oparg**: The argument. Usually the same as the Tier 1 oparg after expansion of `EXTENDED_ARG` prefixes. Up to 32 bits. -- **operand**: An additional argument, Typically the value of *one* cache item from the Tier 1 inline cache, up to 64 bits.