HS: batched conformance runner + JIT cache architecture plan
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tests/hs-run-batched.js — fresh-kernel-per-batch conformance runner.
Solves the WASM kernel JIT-cache-saturation problem (compiled VmClosures
accumulate over a single process and slow tests at the tail of the run)
by spawning a child Node process per batch. Each batch starts with an
empty cache, so tests at index 1400 perform identically to tests at
index 100. Configurable batch size (HS_BATCH_SIZE, default 150) and
parallelism (HS_PARALLEL, default 1).
This is option 2 from the cache-architecture plan — the lowest-risk fix:
zero kernel changes, deterministic results, runs in the same time as the
single-process version when parallelism matches CPU count.
plans/jit-cache-architecture.md — sketches the SX-wide architectural
fix in three phases:
1. Tiered compilation — call counter on lambdas; only JIT after K
invocations. Filters out one-shot lambdas (test harness, dynamic
eval, REPLs) at the source.
2. LRU eviction — central cache with fixed budget. Predictable memory
ceiling regardless of input pattern.
3. Reset API — jit-reset!, jit-clear-cold!, jit-stats, jit-pin!
primitives for app-driven cache management.
Layer split: cache datastructure + LRU in hosts/ocaml/lib/sx_jit_cache.ml
(new), VM integration in sx_vm.ml, primitives registered in
sx_primitives.ml, declarative spec in spec/primitives.sx, and SX-level
ergonomics (with-jit-threshold, with-fresh-jit, jit-report) in lib/jit.sx.
This is host-specific to the OCaml WASM kernel but the SX API surface is
shared across all hosted languages (HS, Common Lisp, Erlang, etc.).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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plans/jit-cache-architecture.md
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# JIT Cache Architecture — Tiered + LRU + Reset API
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## Problem statement
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The OCaml WASM kernel JIT-compiles every lambda body on first call and caches
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the resulting `vm_closure` in a mutable slot on the lambda itself
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(`Lambda.l_compiled`, `Component.c_compiled`, `Island.i_compiled`). Cache
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growth is unbounded — there is no eviction, no threshold, no reset.
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**Where it bites today:** the HS conformance test harness compiles ~3000
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distinct one-shot HS source strings via `eval-hs` in a single process. Each
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compilation creates a fresh lambda → fresh `vm_closure`. After ~500 tests,
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allocation pressure / GC overhead dominates and tests that take 200ms in
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isolation start taking 30s.
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**Where it would bite in production:** a long-lived process that accepts
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arbitrary user-supplied SX (a scripting plugin host, a REPL service, an
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edge function with cold lambdas per request, an SPA visiting thousands of
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distinct routes). Today's SX apps don't hit this because they compile a
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fixed component set at boot and reuse it; the cache reaches steady state.
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## Architecture
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Three coordinated mechanisms, deployed in order:
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### 1. Tiered compilation — "filter what enters the cache"
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Most lambdas in our test harness are call-once-and-discard. They consume
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JIT compilation cost, occupy cache space, and never amortize. Solution:
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don't JIT until a lambda has been called K times.
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**OCaml changes:**
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```ocaml
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(* sx_types.ml *)
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type lambda = {
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...
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mutable l_compiled : vm_closure option; (* unchanged *)
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mutable l_call_count: int; (* NEW *)
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}
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```
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```ocaml
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(* sx_vm.ml — in cek_call_or_suspend *)
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let jit_threshold = ref 4
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let maybe_jit lam =
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match lam.l_compiled with
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| Some _ -> () (* already compiled *)
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| None ->
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lam.l_call_count <- lam.l_call_count + 1;
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if lam.l_call_count >= !jit_threshold then
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lam.l_compiled <- !jit_compile_ref lam globals
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```
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**Tunable via primitive:** `(jit-set-threshold! N)` (default 4; 1 = old
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behavior; ∞ = disable JIT).
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**Expected impact:**
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- Cold lambdas (test harness, eval-hs throwaways) never enter the cache.
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- Hot lambdas (component renders, event handlers) hit the threshold within
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a handful of calls and get full JIT speed.
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- Eliminates the test-harness pathology entirely without touching cache size.
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### 2. LRU eviction — "bound memory regardless of input"
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Even with tiered compilation, a long-lived process eventually compiles
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enough hot lambdas to exceed memory budget. Pure LRU eviction with a
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fixed budget gives a predictable ceiling.
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**OCaml changes:**
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```ocaml
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(* sx_jit_cache.ml — NEW module *)
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type cache_entry = {
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closure : vm_closure;
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mutable last_used : int; (* generation counter *)
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mutable pinned : bool; (* hot-path opt-out *)
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}
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let cache : (int, cache_entry) Hashtbl.t = Hashtbl.create 256
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let mutable cache_budget = 5000 (* lambdas, not bytes — easy to reason about *)
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let mutable generation = 0
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let lookup lambda_id = ...
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let insert lambda_id closure =
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generation <- generation + 1;
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Hashtbl.add cache lambda_id { closure; last_used = generation; pinned = false };
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if Hashtbl.length cache > cache_budget then evict_oldest ()
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let pin lambda_id = ...
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```
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**Migration:** `Lambda.l_compiled` stops being a direct slot; it becomes
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a lookup against the central cache via `l_id` (each lambda already has
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a unique identity). Failed lookups fall through to the interpreter — same
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correctness semantics, just slower for evicted entries.
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**Tunable:** `(jit-set-budget! N)` (default 5000; 0 = disable cache).
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**Pinning:** `(jit-pin! 'fn-name)` keeps a function from ever being evicted.
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Use for stdlib helpers, hot rendering paths.
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### 3. Manual reset API — "escape hatch for app checkpoints"
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Some app patterns know exactly when their cache should be flushed:
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- A web server between request batches
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- An SPA on logout / navigation
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- A test runner between batches (yes, even with #1 + #2)
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- A REPL on `:reset`
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**Primitives:**
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| Primitive | Behavior |
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|-----------|----------|
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| `(jit-reset!)` | Drop all cache entries. Hot paths re-JIT on next call. |
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| `(jit-clear-cold!)` | Drop only entries that haven't been used in N generations. |
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| `(jit-stats)` | Returns dict: `{:size N :budget M :hits H :misses I :evictions E}`. |
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| `(jit-set-threshold! N)` | Raise/lower compilation threshold at runtime. |
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| `(jit-set-budget! N)` | Raise/lower cache size budget. |
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| `(jit-pin! sym)` | Pin a named function against eviction. |
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| `(jit-unpin! sym)` | Unpin. |
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All zero-cost when not called — just a few atomic counter increments.
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## Where it lives
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The JIT is host-specific (OCaml WASM kernel). The plan splits across
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three layers:
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```
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hosts/ocaml/lib/sx_jit_cache.ml NEW — cache datastructure + LRU
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hosts/ocaml/lib/sx_vm.ml Modified — call counter, lookup integration
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hosts/ocaml/lib/sx_types.ml Modified — l_call_count field, l_id is global
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hosts/ocaml/lib/sx_primitives.ml Modified — register jit-* primitives
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spec/primitives.sx Modified — declarative spec for jit-* primitives
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lib/jit.sx NEW — SX-level helpers + macros
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```
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**lib/jit.sx** would contain:
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```lisp
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;; Convenience: temporarily change threshold
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(define-macro (with-jit-threshold n & body)
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`(let ((__old (jit-stats)))
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(jit-set-threshold! ,n)
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(let ((__r (do ,@body))) (jit-set-threshold! (get __old :threshold)) __r)))
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;; Convenience: drop cache before/after a block
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(define-macro (with-fresh-jit & body)
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`(let ((__r (do (jit-reset!) ,@body))) (jit-reset!) __r))
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;; Monitoring helper for dev mode
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(define jit-report
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(fn ()
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(let ((s (jit-stats)))
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(str "jit: " (get s :size) "/" (get s :budget) " entries, "
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(get s :hits) " hits / " (get s :misses) " misses ("
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(* 100 (/ (get s :hits) (max 1 (+ (get s :hits) (get s :misses)))))
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"%)"))))
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```
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This is shared SX — every host language (HS, Common Lisp, Erlang, etc.)
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gets the same API for free.
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## Rollout
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**Phase 1: Tiered compilation (1-2 days)**
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- Add `l_call_count` to lambda type
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- Wire counter increment in `cek_call_or_suspend`
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- Add `jit-set-threshold!` primitive
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- Default threshold = 1 (no change in behavior)
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- Bump default to 4 once test suite confirms stability
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- Verify: HS conformance full-suite run completes without JIT saturation
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**Phase 2: LRU cache (3-5 days)**
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- Extract `Lambda.l_compiled` into central `sx_jit_cache.ml`
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- Add `l_id : int` (global, monotonic) to lambda type
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- Migrate all `vm_closure` accessors to go through cache
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- Add `jit-set-budget!`, `jit-pin!`, `jit-unpin!` primitives
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- Verify: same full-suite run with budget=100 — cache hit/miss ratio reasonable
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**Phase 3: Reset API + monitoring (1 day)**
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- Add `jit-reset!`, `jit-clear-cold!`, `jit-stats` primitives
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- Add `lib/jit.sx` SX-level wrappers
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- Integrate into HS test runner: call `jit-reset!` between batches as belt-and-suspenders
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- Document in CLAUDE.md / migration notes
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**Phase 4: Production hardening (incremental)**
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- Memory pressure hooks (browser `performance.measureUserAgentSpecificMemory`)
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- Bytecode interning (dedupe identical `vm_closure` bodies across lambdas)
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- Generational sweep on idle (browser `requestIdleCallback`)
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- These are nice-to-have, not required for correctness.
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## Testing
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Each phase ships with:
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- Unit tests in `spec/tests/test-jit-cache.sx` (new file)
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- Conformance must remain 100% per-suite
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- Wall-clock benchmark: full HS suite single-process before/after
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Phase 1 acceptance criterion: HS conformance suite completes in single
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process under 10 minutes wall time.
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Phase 2 acceptance: same as 1 but with budget=500. Cache size stays
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bounded throughout the run; hit rate >90% on hot paths.
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Phase 3 acceptance: `jit-reset!` between batches reduces test-harness
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wall time by >50% vs no reset (because hot stdlib stays cached, but
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test-specific lambdas don't accumulate).
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## Why this order
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Tiered compilation is the highest-leverage change — it solves the
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test-harness problem at the source (most lambdas never enter the
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cache) without touching cache machinery. LRU is the safety net
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(unbounded growth still possible if every lambda is hot, e.g., huge
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dynamic component graph). Reset is the escape hatch for situations
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neither mechanism can handle (logout, hard memory pressure, app
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restart without process restart).
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Doing them in reverse would invert the value — reset alone fixes
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nothing without app-level integration, and LRU without tiered
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compilation churns the cache constantly on cold lambdas.
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