Graphite/node-graph/rfcs/attribute-model.md

Summary

Give every item flowing through the graph a set of named, typed attributes next to its primary element value. Attributes are stored as a packed record whose layout the compiler computes at graph compile time. Nodes declare their attribute reads and writes in their signatures, and the compiler resolves every access to a byte offset during wiring, so there is no name lookup at runtime. Storage and batch results are per-attribute columns. The contiguous record only exists as a per-lane view, assembled into activation frames on a per-thread stack. All of the machinery that could corrupt a layout is generated code, so getting it wrong is a type error or a graph compile error rather than undefined behavior.

Motivation

Attributes currently exist as a string-keyed store of type-erased columns beside the elements:

pub struct List<T> {
	element: Vec<T>,
	attributes: Attributes,
}

struct Attributes {
	attributes: Vec<(String, Box<dyn AnyAttribute>)>,
	len: usize,
}

So the storage is already columnar: one boxed column per name, each holding len values. What it is not is resolved. Every access searches the key list by string comparison and downcasts the column, and merging eagerly pads missing attributes with materialized defaults. Scalar access boxes per value at the item boundary, where the same store appears as ItemAttributeValues(Vec<(String, Box<dyn AnyAttributeValue>)>). On a ten-node chain with eight attributes over 64k items this costs us around 500ns per item. The design described here measures between 3.5 and 47ns on the same workload, depending on the execution mode, and the cost is mostly independent of the attribute count.

There is also a cost at compile time and in the node catalog. Because attributes ride inside List<T>, a node that touches a property carries an implementations list enumerating every carrier type: the opacity and blend-mode nodes each name seven. Each row monomorphizes, adding a new carrier type means editing every one of these lists, and the duplicated instantiations show up in the build size, measured at 6.16 MB and about 4% of frame rate when the rank work landed. An escape hatch exists for the narrow case of reading an attribute without the element (ListDyn, which erases the carrier), but it does not extend to nodes that write. Separately, opacity on a group and opacity on each member composite differently once members overlap, so the two are semantically distinct and the representation has nowhere to record which one a node meant.

The requirements, briefly. Attributes are named with strings and work for all types, and users can author read/write nodes with custom names. A node placed before vs. after a structure node affects different nesting levels. Items whose element types agree can merge regardless of their attribute sets, with missing values filled from name-specific defaults. Names resolve at graph compile time, with a dynamic escape hatch for runtime-shaped data. A wire without attributes costs what a plain wire costs, and an attribute that is constant across a domain costs one slot rather than one per element. Batch access is the case to optimize, and scalar access should not require a second representation with conversions between the two.

Guide-level explanation

What an attribute is

An item is a primary value (the element, which determines the wire's type and colour) plus a set of named attributes that flow along with it. A node can read, add, or overwrite one attribute without touching the element and without knowing which other attributes exist. Lists carry attributes at every nesting level, so an attribute on a group is a different thing from the same attribute on the group's members.

Declaring an attribute

An attribute name is declared once, as a marker type:

attribute! {
	/// How visible the content is.
	pub Opacity("opacity"): f64 = 1.;
	/// The item's label, parked in the arena by the writer.
	pub Label("label"): &str;
}

Each entry expands to the marker struct, its Attribute impl, and the census registration. This fixes the name, the value type, and the name-specific default (opacity should default to fully opaque, not to f64::default()). The registry collects the declarations into a census, and a misspelled name in a document can be diagnosed with a nearest-match suggestion. For names declared in code, one name belongs to one marker, so a name can never mean two different types. For user-supplied names, the marker fixes the value type and the default in code, while the name itself arrives as a constant text input on the document node. It joins the name table at graph compile time, which is where every resolution happens anyway, and two user-supplied names colliding at different value types is a graph compile error naming both nodes.

A write can also be generic over both the name and the value type. The attribute then arrives on its own wire, as an input whose element is ():

/// Attaches the attribute to the content.
#[node_macro::node(category("Attributes"))]
fn set_attribute<T, A, Y>(
	_: impl Ctx,
	element: T,
	(_, attr): ((), Attr<Custom<A, Y>>),
) -> (T, Attr<Custom<A, Y>>) {
	(element, attr)
}

A unit value component means the edge exists and carries only its attributes (_: () still means no edge at all). The name enters the graph at a source node holding the constant text input, whose output type is filled at graph compile time, where user-supplied names join the name table anyway; the compiler pairs A and Y through the wire types, so the write set is derived from types alone, and the one-name-one-type check covers the binding, making a declared name targeted at a different type a graph compile error. A generic read resolves only when the input wire's type determines the binding uniquely, and anything else is a validation error. The node is one compiled instance: A and Y instantiate with tokens and the value rides the copy plan as a byte move, parked in the arena when its type has drop glue, so no implementations list exists. A kernel that computes on the value uses a bound and monomorphizes per its implementations list as usual.

Reading and writing attributes

A node declares its attribute io in its signature. A parameter that reads attributes destructures its input into the wired value and the reads taken from that input's wire. The opacity node becomes:

/// Modifies the opacity of the input by multiplying the existing value by this percentage.
#[node_macro::node(category("Blending"))]
fn opacity<T>(
	_: impl Ctx,
	(element, opacity): (T, Attr<Opacity>),
	/// How visible the content should be, from 100% (fully opaque) to 0% (fully transparent).
	#[default(100.)]
	factor: Percentage,
) -> (T, Attr<Opacity>) {
	(element, Attr(*opacity * factor / 100.))
}

An Attr<A> inside a parameter tuple is a read from that parameter's wire (it yields the declared default if nothing upstream wrote the attribute), an Attr<A> in the return tuple is a write, and the same marker on both sides is a modify. A RemoveAttr<A> in the return tuple is a delete: the name leaves the output layout, downstream reads yield the default again, and the column leaves the Data panel. A read binds to the input it is destructured from, so which wire an attribute comes from is always explicit in the signature, and secondary inputs declare reads the same way:

	(factor, out_of_100): (Percentage, Attr<OutOf100>),

There is no implicit attribute flow between inputs. The primary input's attributes pass through to the output, overwritten where the node writes; a secondary input contributes exactly the reads its tuple names. An input without reads stays a plain parameter. Parameter attributes (#[default], #[implementations], doc comments) apply to the value component; attribute markers are concrete types and never enter monomorphization.

The first parameter after the context is the primary input, with or without a read tuple, and an unbounded generic element: T in its value position that is returned in the first tuple position means "I pass the element through unchanged". The compiler lowers this to a byte copy (often to nothing, see below), and a single compiled instance covers every element type, with no trait bounds and no implementations list. A node that actually computes on the element uses a concrete type or a bound instead and monomorphizes per its implementations list. _: () means "no primary input".

Levels: before vs. after a structure node

This part of the design is not settled, and the first implementation resolves every attribute at a single level. It is written up here because the requirement is real and the rest of the model has to leave room for it; see the open question at the end.

Where a node sits in the chain should decide which nesting level it affects. Applying the opacity node to a shape and then repeating it would give every copy its own opacity. Repeating first and then applying opacity would set one value on the whole group, which composites differently where copies overlap. The node's code is identical in both cases. Reads and writes bind to the top level of the wire at the node's position in the chain, and Repeat pushed a level in one of the two arrangements. Reaching an inner level from outside is an explicit map/enter construct, so "set on the parent" and "map over the children" are visibly different graphs.

Structure nodes

A node that produces a list declares the new level's extent and writes per-copy values. The body is one lane of that list. There are two shapes, and which one applies is decided by whether the copies have to re-evaluate the content.

The general shape takes the content lazily and evaluates it once per copy, at that copy's index:

/// Instances the content a number of times, spaced by the direction vector.
#[node_macro::node(category("Repeat"), extent(repeat_extent))]
fn repeat<T>(
	ctx: impl Ctx + DeriveCtx + ExtractIndex,
	content: impl Node<Context<'_>, Output = (T, Attr<Transform>)>,
	#[default(1)]
	#[hard(1..)]
	count: u32,
	#[default(100., 100.)]
	direction: DVec2,
) -> Result<IList<(T, Attr<Transform>)>, Interrupt> {
	let inner = content.inner_extent(ctx)?;
	let (copy, rest) = ctx.split_innermost(inner);
	if copy >= count as u64 {
		return Err(GraphError::past_end().into());
	}
	let offset = direction * copy as f64;
	let mut frame = IndexLink { index: 0, outer: None };
	let (element, transform) = content.eval(&ctx.push_level(&mut frame, copy, rest))?;
	Ok((element, Attr(DAffine2::from_translation(offset) * *transform)))
}

The kernel splits the flat index into its own copy index and the index below it, then evaluates the content at a context with the copy pushed as a level. DeriveCtx is what admits the push, and only a lazy input can receive a derived context, so this shape is exactly the one where the copies are allowed to differ: anything upstream that reads the index sees the copy it is being evaluated for.

Where the copies do not re-derive the content, the input stays an ordinary carrier and the kernel only computes the copy's own attributes:

#[node_macro::node(category("Repeat"), extent(repeat_opacity_extent))]
fn repeat_opacity(ctx: impl Ctx + ExtractIndex, element: f64, count: u32) -> IList<(f64, Attr<Opacity>)> {
	emit(element, Attr(ctx.index() as f64))
}

A carrier is evaluated once for the whole run rather than per lane, so every copy sees the same element and the variation lives entirely in the attributes. The emit(...) tail marks the one-lane form and doubles as the tuple constructor, and it is optional.

Merging

Merging concatenates. The merged attribute set is the union of the inputs', and an attribute missing on one side is filled with its declared default for that side's items, so the result is rectangular in every attribute. A scalar input contributes one item. When lists are combined, each input's own top-level attributes are pushed down onto that input's items (composing by the attribute's declared rule where one exists; otherwise the pushed value fills the items that never wrote the name and the inner value wins where they did, resolved from the write sets at graph compile time), and the merged list starts with an empty top level. If the user wants to keep the groups as groups, they wrap explicitly instead.

Selecting

Switch takes two lazy inputs and returns one of them, for any carrier, without an implementations list:

/// Evaluates either the "If True" or "If False" input branch based on the condition.
#[node_macro::node(category("Math: Logic"))]
fn switch<T>(
	ctx: impl Ctx,
	_: (),
	condition: bool,
	#[expose]
	if_true: impl Node<Context<'_>, Output = T>,
	#[expose]
	if_false: impl Node<Context<'_>, Output = T>,
) -> T {
	if condition { if_true.eval(ctx) } else { if_false.eval(ctx) }
}

An unbounded generic on a lazy input means the whole record flows through. Evaluating a branch yields an opaque value carrying its record, and whatever value the kernel returns is the output, element and attributes together. Kernels can evaluate several inputs, hold the results side by side, and pick among them with any logic, so fallback, N-way multiplexers, and per-lane data-driven selection are the same two-line pattern rather than new node kinds. The branches may carry different attribute sets. The output carries their union, filled with defaults per branch. A lazy input with a concrete output type is an ordinary value input: its value flows, the attributes on its wire do not. The tuple form composes with laziness: a lazy input declared Output = (T, Attr<A>) yields the element and the declared reads at each evaluation, so a kernel can branch on another input's attribute without evaluating the branch it rejects. It is a read declaration only: the lazy input's fields do not pass through to the output, since the kernel controls whether and how often the edge is evaluated; forwarding a lazy input's attributes is routing.

The rest of the authoring surface composes. Categories, per-parameter doc comments, #[default], #[hard], #[expose], widget overrides, and the kernel dialects (Result<_, Interrupt> with ?, GPoll returns, async sources) all compose with the forms above.

Reference-level explanation

Records and layouts

A record is the element at offset 0 plus one field per written attribute, aligned to the widest field. Since the element comes first, a pointer to the record is also a valid pointer to the element. Element-only consumers are wired without adaptation, the wire keeps the element's type and colour, and the registry stays keyed on element types.

  byte  0       4       8      12      16      20      24      28   31
        ┌───────────────┐
  f64   │    element    │
        └───────────────┘

        ┌───────────────┬───────────────────────────────┬───────┬─┬───┐
  +3    │    element    │      Attr<&str>  (ptr, len)   │  u32  │b│pad│
        └───────────────┴───────────────────────────────┴───────┴─┴───┘

  Canonical order (descending alignment, then size) leaves no interior
  padding here; 3 bytes of tail round the record up to align 8.

A wire's layout is the set of all attributes written in its upstream cone and not removed since, in a canonical order (descending alignment, then size, then name and level), computed at graph compile time. Some consequences:

• Layout identity is captured by stable node ids, because the write set is part of the hashed upstream cone. An instance that survives an incremental recompile cannot meet a changed layout.
• Reads resolve to Option<offset> at wiring, each against the layout of the input wire its tuple destructures. Present means a field access, and absent means the macro emits the default constant. Writes always resolve. The runtime does no name lookup, no hashing, and no downcasting. A resolved read costs the same as a native struct field access (0.43ns).
• Writes that are never read are diagnosed. Eliding them is a permitted whole-graph optimization but not required. Keeping them in the layout is what keeps the layout a pure function of the upstream cone.
• Layouts are derived data. The document stores only user-visible structure, no attribute data is serialized, and representation changes never require a document migration.
• Semantically a wire value has every attribute at all times: a read of a name nobody wrote yields the declared default, so a written default and an absent name are indistinguishable at runtime. Presence (membership in the layout) is representation, consulted only by merge push-down's fallback and the Data panel, which presents the layout: column presence is a pure function of the graph, stable across frames and across the branches a selector takes.
• Writes are unconditional: presence never depends on a value, so a conditionally relevant attribute is written at its default, and a runtime Option around a value buys nothing (None could only mean the default). A name that wants a distinguished unset declares an Option value type on its marker.

Fields are Copy, and larger payloads go behind a pointer-sized field. Runtime-shaped data (CSV columns, arbitrary JSON) is a single dynamic attribute holding a map in a fixed-size slot. It is the intended slow path and puts no constraints on the fast one. Layouts are always static.

A name's type is unique by construction. For declared markers the census admits one marker per name, checked when the registry is built. For user-supplied names the binding forms at graph compile time, carrying the marker's declared value type, and two names colliding at different types is a graph compile error that names both nodes. Generic-typed writes join the same table, carrying the name and value type their bindings resolve to, so the check runs over declared markers, user-supplied names, and generic instantiations together. We do not attempt coercion.

Levels and residency

Layout keys carry a level, and levels are numbered from the innermost out, which keeps them stable when a structure node pushes a level (nothing renumbers) and matches how indices are already numbered. Only level 0 is populated today: the packed-record tier is flat, so the binding rules below and the residency analysis that follows them are the intended design rather than the implemented one. The level in the key is what leaves room for both.

The binding rules are:

• A read binds to the top level of the input wire it is destructured from at the node's chain position; a write binds to the top level of the output wire.
• A structure node pushes a level and then writes its per-copy attributes into the former top row, and the new top row starts empty.
• A node that reads the element (concrete type or bound) is pinned to level 0. An element-agnostic node binds to whatever the top currently is, which is also what allows a pure attribute node to run at a level where no element is materialized at all.

An attribute at level j ignores indices deeper than j by definition, so the level a value's storage actually varies with (its residency) lies somewhere between its binding level and the root. The compiler computes residency with the same index-invariance analysis used for context nullification. Constant-everywhere is residency at the root: one slot. A per-item attribute that only varies per group is bound at level 0 but resident at level 1, so it gets one slot per group rather than one per item.

Storage is meant to be level-resident and columnar, with the contiguous record as a view. Per-lane consumers get the view assembled across levels and columns into their activation frames. Reads across a level boundary use the same index decomposition the structure nodes already perform, and in batches that decomposition is hoisted per run. Neither the residency analysis nor the multi-level storage exists yet; a single level with resolved offsets is the base case both are built on.

Runtime representation

• Every node's per-lane output is an activation frame on a per-thread record stack, callee-fills-then-reclaims discipline: an evaluation claims its frame at the stack pointer, evaluates its inputs beyond it, writes its result into the frame, and then reclaims everything above the frame while keeping the frame itself for its consumer. So a node advances the stack by exactly its own frame, and every already- evaluated input stays live until the node returns, which makes values held across sibling evaluations safe by construction. "Allocating" a result is pointer arithmetic; transients never touch the arena, and publishing into a cache copies out of the stack. An inline node returns its output by value with no frame, so it reclaims its inputs by rewinding to its entry pointer instead. A loop that re-evaluates a subtree per iteration rewinds to a checkpoint each time, reusing the slots.
• No global slot assignment exists: a node's wiring state is its own frame size, so incremental recompiles and instance reuse cannot invalidate storage, and the stack belongs to whichever thread runs the evaluation, created lazily in thread-local storage, so worker counts never enter wiring. The reserve is the peak of a per-path fold over the graph (a node's need is its own frame plus its inputs' frames plus the deepest input's peak), computed once at wiring; it exceeds the plain sum of node frames because fan-out re-evaluation keeps several copies of a shared node's frame live at once.
• Held record values are safe without a guard: a frame keeps its output until its consumer reclaims it, so no input is released while a later sibling evaluates. This relies on stack records being single-consumer, which the frame-memo insertion at fan-out points guarantees by copying a shared value off the stack rather than holding it across consumers.
• Batch results are a run of lanes behind a resolved offset per field, and the target form is per-field columns, each statically Varying (an array) or Uniform (a single value) per the residency analysis. A node that does not touch a column then forwards the pointer, so bypass costs nothing, and uniform columns give constant attributes their one-slot cost regardless of lane count. Both execution forms share one layout descriptor, and crossing from a batched producer to a per-lane consumer costs about 1.5ns per lane through a lane-view adapter. The first implementation lays the run out as an array of records and resolves each marker to an offset within a lane; moving that to struct-of-arrays, and then to flat tables, happens behind the same accessors.
• A materialized level carries its lane count beside its layout and its storage, which is either an arena-resident run or an owned copy. Erased consumers (the Data panel, capture, deep copy) read the count and the fields off that handle without reaching into the element type, and Varying vs Uniform is meant to stay static in the layout, a Uniform column addressing a single value. This is the same picture as a batch result, so materializing a level and returning a batch are one format. A record value is one pointer wide, and only a record whose layout is empty rides inside the value itself; everything else spills to the stack.
• Alignment padding is what the column form buys. In a row, a u8 element costs the same as a u64, while packed columns keep the cost proportional to the element size (2x cheaper than rows when cache-resident, around 8x when memory-bound). Once columns are the storage format, the proportional cost holds wherever data accumulates and the padding survives only in transient view slots, whose number is bounded by graph depth. Until then a run pays a row's padding on every lane, which is the cost the struct-of-arrays step removes.

Kernel io lowering

Signature form	Meaning	Lowering
first non-context param	primary input	carrier record
_: ()	no primary input	no carrier edge
element: T (unbounded, returned first)	explicit passthrough	erased byte carry, where T is instantiated with a zero-sized token, so the routing is checked by the type system and costs nothing
element: Concrete / bound	element read	field read at offset 0, monomorphized per implementations list, binds level 0
(x, a): (X, Attr<A>)	input with attribute reads	the value as its ordinary lowering; each Attr an offset read into that input's record, or the default constant
(_, a): ((), Attr<A>)	attribute-only input	wired record edge with unit element; the attribute is the payload
Attr<A> in the return tuple	attribute write	offset write into the output record
RemoveAttr<A> in the return tuple	attribute delete	the name leaves the output layout; functionally a write of the default
keys: IList<K>	whole-extent input	wired edge, evaluated over its extent into a view
plain parameters	wired value inputs	ordinary wired edges; attributes on their wires do not flow
impl Node<Context<'_>, Output = Concrete>	lazy value input	the value flows, attributes do not
impl Node<Context<'_>, Output = (T, Attr<A>, ..)>	lazy input with attribute reads	each eval yields the element plus the declared reads, offsets resolved against that edge's layout; a read declaration only, and no field pass-through
impl Node<Context<'_>, Output = T> (unbounded)	source of an opaque record family	routing, see below
-> IList<W> with a lazy subject and DeriveCtx	per-copy level production	the kernel splits the index and evaluates the subject at the pushed level
-> IList<W> with a carrier subject	per-lane level production	the carrier binds once for the run; the kernel computes each lane's own fields
-> IList<W> without extent(fn)	store form	whole-level body, node owns storage

extent(fn) names a function over the node's inputs and the queried level (author code never receives the node struct); extent_raw(fn) is the escape hatch for anything that vocabulary cannot say. The declaration answers what the level's counts are; the kernel performs the matching index decomposition itself. The two are written separately and have to agree, which is why the split and push go through shared helpers rather than open-coded arithmetic. emit(...) is an optional tail marker for the carrier form whose parentheses double as the tuple's, so multi-write lanes pay no extra nesting.

The rule behind all the lazy forms: kernels control whether, when, and at which index their inputs are evaluated, but never how the records move. Attributes travel inside record values or through generated machinery, so kernel-controlled evaluation cannot misalign them, and domain declarations stay with the extent system.

Structure shapes

A structure node pairs an extent composition with an index decomposition. The extent composition is an ordinary extent override: the node macro's extent(fn) attribute names a function over the node's inputs and the queried level to GPoll<Extent>, with extent_raw(fn) as the escape hatch keeping the raw node, context, and level form, so multiplicative, additive, and data-dependent extents are one mechanism rather than a macro taxonomy, and the default stays the meet over the value inputs.

• Multiplicative (Repeat, map/enter): the extent override answers the pushed level with the copy count and forwards inner levels to the content. The kernel splits the flat index into the copy index and the index below it through the shared split helper, and pushes the copy as a level on a derived context before evaluating the content there. The extent declaration and the split are written separately and have to agree; the helpers are shared so that they can. Batches split into maximal per-copy runs.
• Additive (Merge): an ordinary routing kernel whose selector condition is the index. The kernel range-splits the flat index into a segment and a local index through the shared split helper and evaluates that input at the shifted index via the derived-context lowering; the extent override sums the inputs' extents through Extent::sum. An input with unbounded (Free) extent counts as exactly one item in the sum, so merge is an extent-forcing boundary, which is the scalar base case. Item rows union with per-segment default fill. Each input's top row is pushed down one level onto that input's items via entries in the translation plan (a level remap computed at wiring; no values are needed at compile time), composing by the declared combine rule; the fallback is inner wins iff the inner level wrote the name, resolved from the write sets at wiring. The merged top row starts empty. An explicit Wrap node is how the user nests instead; a marker on the merge node enables the push-down plan variant. Batched merge forwards per-segment sub-ranges derived from the same split helper, so column uniformity survives concatenation per segment, default materialization is only paid on the per-lane and store paths, and per-lane vs batched agreement is law-bound.

Opaque record values

An unbounded generic names a family of opaque record values. Its sources are the lazy inputs whose Output is the generic; the element passthrough is the same mechanism with the carrier as the family's only source. Wiring computes the union of the sources' layouts and a translation plan per source (field moves plus default fills). The kernel-facing handles wrap the edges the same way the error dialect wraps status plumbing: evaluating a source evaluates its edge at the unchanged context and yields a value carrying the resulting record, either through the plan into that source's own buffer, or, when the source's layout already equals the union, by forwarding the record pointer untouched. The forwarding case compiles to a conditional move plus a tail call; the +4.7ns per lane of a two-branch switch is the condition and ordinary branch misprediction, and a translating source costs +6.5ns per lane at eight attributes.

The kernel routes these values as ordinary Rust values. It can evaluate any source any number of times, hold several results at once (per-source buffers keep them valid side by side), pass them through helper functions, and return any of them. The returned value's record is the node's output, so provenance is carried by the value itself: element and attributes travel together, and returning a result obtained before some later evaluation is well-defined. A value is live until its own source is evaluated again, which overwrites that source's buffer; a kernel that needs two results of one input side by side declares the input twice. The values are opaque and unforgeable, and inspecting one requires bounds on the generic, which is element access and monomorphization as usual.

This is the general form of selection: switch, fallback, N-way multiplexers, and per-lane data-driven choice among inputs are all plain kernels over the same mechanism, and none of them needs anything from the macro beyond the family lowering. Whole-list switching vs. per-item zip is just the residency of the condition: an invariant condition collapses through nullification, a varying one selects per lane.

The one-source shape also covers the registry's infrastructure rows. Monitor, context modification, memoize, and the lend and clone adapters are all T -> T passthroughs with a side effect. Over the record family each is a single generic node: the record forwards, and the side effect is orthogonal to the type (a reflective snapshot through the layout descriptor, a derived context, or a persistence copy sized by the layout). Persisting a non-Copy element needs a clone and drop function per element type, registered once beside the type itself rather than once per infrastructure node, so the per-type surface is types plus nodes rather than types times nodes, and compiler-inserted infrastructure splices one generic proto node without naming value types. The genuine conversion rows (the Into and Convert matrix) remain, because those do real per-type work.

A kernel that modifies the index on the context evaluates an input at a lane other than its own, which makes index-computable reorders plain kernels:

/// Reverses the order of the input list.
#[node_macro::node(category("General"))]
fn reverse<T>(
	ctx: impl Ctx + ModifyIndex + Copy,
	_: (),
	content: impl Node<Context<'_>, Output = T>,
) -> Result<T, Interrupt> {
	let total = match content.extent(ctx, Level::Total) {
		GPoll::Final(Extent::Exactly(count)) => count as u64,
		GPoll::Pending => return Err(Interrupt::Pending),
		_ => return Err(GraphError::new("reverse over a non-exact extent").into()),
	};
	let mut shifted = *ctx;
	shifted.set_index(total - 1 - ctx.innermost_index());
	content.eval(&shifted)
}

Shift, slice, and read-item-at-index are the same shape. Sort and shuffle still compute a whole-extent permutation once per sweep, which a pure per-lane kernel cannot hold, so they keep the remap-returning kernel. Applying a remap has a spec: per lane, evaluate the input at the permuted index. The generated batch kernel is the law-bound override of that spec, materializing the input's columns once and gathering each index-varying column through the wiring-resolved table with index-invariant columns skipped (about 1.4ns per varying column per lane; the comparison work of the sort itself does not depend on the representation). For a bijective permutation the per-lane spec already costs the same number of upstream evaluations as direct consumption, so the batch form buys cache locality and run coherence rather than correctness.

Compiler passes

Everything happens at graph compile time. The census is assembled from the marker declarations (names, types, defaults, combine rules). Each wire's layout is constructed from its upstream write set, and residency comes from the index-invariance analysis. Offsets are resolved into node state, the stack bound is folded from the layouts, and union and translation plans are built at selectors and merges. A per-name dependency analysis feeds the cache keys. The diagnostics produced along the way are unknown or misspelled names (checked against the census, with nearest-match suggestions), custom-name collisions, reads that some evaluation path cannot satisfy, and layout conflicts. The runtime does no name lookup. Layout construction and the safe record builders check field type identity and panic on a mismatch, which is what guards the generated code against itself at wiring boundaries.

Soundness

Attributes only move through generated machinery. Kernels receive dereferenced values and opaque handles, and the translation and carry plans behind them are emitted from wiring-resolved layouts. Layout identity is captured by stable node ids, so an instance that survives a recompile can never meet a changed layout. Because layouts are functions of wires rather than of anything a kernel controls, safe kernel code can make semantic mistakes (evaluating an input it did not need to) but cannot misalign an offset. Kernels see contexts only as an opaque impl Ctx + ... they cannot construct, and lifetimes keep them from stashing handles in node state.

That is the property the design is for, and reaching it is work rather than a consequence. Type identity is stamped on every layout field and checked where layouts are built and where the safe builders write, which is the enforcement this rests on. What is not yet closed, and is tracked as such: a producer whose layout was never installed writes through a path that assumes the inline width, an owned record replays against a caller-supplied layout it does not check, and the record stack's own bounds check is a debug assertion while its buffer can be reset under live records. Each is reachable from safe code, so the claim above holds by the discipline of the generated code and not yet by construction. The direction is to replace the emitted raw operations with a small set of checked surfaces, so that the remaining unsafe is the erased glue and the wiring-computed byte plans, where it is irreducible.

Drawbacks

• The node macro absorbs real complexity: io classification, layout bookkeeping, the structural skeletons, and the record-family lowering are all generated code. That is the point (authors stay simple, the privileged surface stays auditable), but macro diagnostics will need work to stay better than raw trait-solver errors.
• Changing a document's attribute set changes layouts, which recompiles the affected cone and reconstructs its instances. This is the same cost class as editing node parameters today, but a runtime-map design would absorb attribute renames without recompiling.
• Until an elision pass exists, attributes that are written but never read occupy slots and copies.
• Per-lane views pad small elements up to the record alignment, and so does a run of records until the columnar storage arrives; only the column form is footprint-proportional.
• Two execution forms (per-lane views and batches) are more machinery than one representation. They share a single layout descriptor, and the measured seam between them is about 1.5ns per lane, but the machinery still has to exist.

Rationale and alternatives

• Keep runtime maps (the current implementation): roughly 500ns per item on the reference chain and ~57ns marginal per attribute, an allocation per column, and no compile-time name checking. Interning the keys improves the constant (about 1.9ns per access vs. 0.43 for a resolved offset) but keeps a per-access search and rules out the structural optimizations that need static layouts: bypass, uniform columns, and packing a level's fields to their resolved offsets.
• Attributes as separate graph edges, one channel per attribute: bypass and per-channel caching become graph structure. We prototyped and measured this. Without caching at fan-outs, every channel re-evaluates the shared upstream work (2-4x slower on realistic chains), and the cache that fixes it stores a multi-channel result, which is a record, so the fixed version converges on this design while keeping the extra edges, dispatch, and graph inflation. The two structural insights of the channel model survive here as the column structure of batch results.
• Typed attribute tuples in the wire type: layouts become document-dependent types, which the registry's precompiled constructor rows cannot cover, and row polymorphism leaks into type resolution. Keeping layouts as side metadata means attribute sets never gate convergence (merge unions them, defaults answer switch mismatches) and the resolver is untouched.
• The numbers cited throughout come from a reference prototype with type-erased node edges (the indirect calls were verified in the disassembly), thin LTO, 64k-lane workloads, and best-of-nine timing. Chain results use ten nodes and eight f64 attributes.

Prior art

Attributes were specified in issue #3779 and first implemented by the Item and List wire types work, which remains the behavioral reference for this design: name-specific defaults, merge with default fill, and the Data panel's presentation of items all carry over, and the wire rank display and Data panel belong to the editor and are unaffected here. One behavior is refined rather than kept: flat merge has to drop one input's top-level attributes, which the push-down rule is meant to preserve. The present representation (string-keyed storage inside List<T>, with per-carrier implementations rows) is what the Motivation section measures. This RFC keeps its observable behavior while replacing the storage and registration strategy underneath.

Outside Graphite, the nearest prior art is row polymorphism in records (Rémy; PureScript and Elm) for the layout unions, ECS archetype storage for resolved column handles, and the uniform vs. varying distinction from shading languages for residency.

Unresolved questions

• Leveled attributes, the largest open area. Attributes at more than one nesting level are designed but not built: the layout key carries a level, and nothing populates a level above 0. Open within it are the binding rules as stated (does a read really bind to the top level of the wire it is destructured from, and is pinning element-reading nodes to level 0 the right rule), how a structure node's per-copy write lands in the former top row, whether residency is worth its analysis or whether the extent machinery already answers it (an attribute whose index function ignores the index is Free), and what the storage for a level above 0 looks like given that the record tier is flat. The UX half of the same question is the map/enter construct: how "set on the parent" and "map over the children" read differently in the graph. Until this is settled, the Repeat-around-Opacity requirement is unmet.
• Where and how the combine rule is declared on the attribute marker. Merge push-down and flatten both consume it, and inner-wins is the intended fallback.
• The spelling of the push-down marker on the merge node, the one part of the additive shape the extent override cannot express.
• Naming: Attribute trait vs. Attr wrapper. The authoring list type is spelled IList here, as in the implementation, to keep it clear of the legacy wire type's List; a rename to List is planned once that type retires.
• Generic-typed writes: where the default for a generically written name comes from (a Default bound on the value vs. an input on the name source), what A instantiates to at the Rust level, whether attribute-only wires carry exactly one attribute by construction or uniqueness is checked per read, and the graph UX of the name source node.
• Whether evaluating at a lane outside the input's extent is clamped, wrapped, or a debug assertion.
• IList<IList<W>> outputs, i.e. one node pushing two levels.
• How chatty the editor boundary becomes per frame, given that tools consume materialized views today.

Future possibilities

• Scope variables: varargs with graph-compile-time-known names, the context-side mirror of this design. The same census and marker machinery, reads resolved to a hop count into a stack-allocated chain (0.43ns through two hops in our measurements), pushes that are free of allocation (0.56ns), and injection handles that make a missing or doubled push unrepresentable. This shrinks the context to a hot core and replaces coarse context features with per-name dependencies in cache keys.
• Write elision for never-read attributes, once the whole-graph analysis pass exists.
• Mask-run decomposition in the selector's batch kernel: dense sub-ranges for uniform condition runs, and optionally compute-both-and-select speculation, which purity makes legal.
• GPU consumption: uniform vs. varying columns map directly onto constant buffers vs. vertex attributes.
• A user-routable remap value (shuffle, manual orderings, an apply-remap node) built on the sort machinery.