20a18322b3
The per-site inline cache (#237) resolves a statically-proven monomorphic devirt once instead of per call, so mono-dispatch is no longer worse than megamorphic. The remaining dispatch lever is the megamorphic case (a runtime receiver-type-keyed cache).
89 lines
4.7 KiB
Markdown
89 lines
4.7 KiB
Markdown
# jolt benchmark suite
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Benchmarks that isolate the workload axes jolt's optimizing passes target. The
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ray tracer (`examples/ray-tracer`) is **float-compute-bound** — its time is
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irreducible algorithmic math (hit-testing + transcendentals), and devirt,
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allocation removal, and type-proving all measured **flat** on it. So it can't
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tell us whether those passes work. These benchmarks make each pass's target
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workload the *dominant* cost.
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Reference: the cross-language suites these draw from —
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[Are We Fast Yet?](https://github.com/smarr/are-we-fast-yet) (Marr et al., DLS '16)
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and the [Computer Language Benchmarks Game](https://benchmarksgame-team.pages.debian.net/benchmarksgame/).
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The benchmarks are portable Clojure, so they also run on JVM Clojure for an
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absolute reference.
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## Benchmarks
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| Benchmark | Axis | Pass it exercises | Source |
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|---|---|---|---|
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| `binary-trees` | allocation / GC pressure (escaping short-lived records) | scalar-replace, escape analysis | CLBG |
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| `dispatch` | polymorphic (**megamorphic**) protocol dispatch | devirt, inline-cache | AWFY-style |
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| `mono-dispatch` | **monomorphic** protocol dispatch (devirt/inline-cache *can* fire) | devirt, inline-cache | AWFY-style |
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| `collections` | persistent map/vector churn (HAMT / 32-way tries) | persistent structures, transients | CLBG k-nucleotide-style |
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| `mandelbrot` | pure float compute (tight arith loops, no alloc/dispatch) | native arith, loop codegen | CLBG |
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| `fib` | recursion: function-call + integer-arith overhead | native arith, small-fn inlining | CLBG |
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What the ray tracer does **not** capture and these do: allocation as the
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bottleneck (~7% there), megamorphic *and* monomorphic dispatch (its dispatch is
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monomorphic and cheap), persistent-collection throughput (it uses fixed records,
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no collections in the hot loop), and isolated compute/call overhead.
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Planned additions: Richards / DeltaBlue (heavier OO dispatch), NBody (float
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control with record state), k-nucleotide proper.
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## Holistic scorecard
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`bench/run.sh` compiles each benchmark to an **optimized AOT binary** (`joltc build
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--direct-link --opt`) and times it against JVM Clojure running the same portable
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source — the jolt/JVM scorecard. jolt's optimizing passes fire only in a build;
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`joltc run -m` is unoptimized, so the harness always builds.
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Indicative ratios (M-series, single isolated run — numbers are machine-specific,
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regenerate locally), ascending:
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| benchmark | ratio | axis |
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|---|---|---|
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| `fib` | ~0.6× | call + integer arith |
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| `collections` | ~3.5× | persistent map/vector churn |
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| `mandelbrot` | ~7.5× | pure float compute |
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| `binary-trees` | ~10× | escaping short-lived records (allocation/GC) |
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| `dispatch` | ~12× | megamorphic protocol dispatch |
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| `mono-dispatch` | ~15× | monomorphic protocol dispatch |
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- **Compute (~0.6–7.5×)** is the substrate floor: Chez is a native-compiling AOT
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Scheme, not a profiling JIT. With native arith + direct-linking + inlining jolt
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is at parity here — `fib` runs *faster* than JVM Clojure (no JIT warmup over a
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short run), `collections` is within ~3.5×, and `mandelbrot` (~7.5×) is the
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pure-tight-loop float ceiling that only native codegen moves further.
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- **Dispatch & allocation (~10–15×)** are the remaining architectural gaps, though
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the type-proving / native-record / bare-field-read work has collapsed them by an
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order of magnitude (`binary-trees` ~140×→~10×, `mono-dispatch` ~330×→~15×). On a
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*statically proven* monomorphic receiver — which whole-program inference now gives
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for a record iterated out of a vector — devirt resolves the impl and a per-site
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inline cache holds it (resolved once, not per call), so `mono-dispatch` is no
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longer worse than megamorphic. The remaining lever is `dispatch`: a *megamorphic*
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site has no static type, so it pays a full protocol-registry lookup every call
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where the JVM uses a polymorphic inline cache — a runtime (receiver-type-keyed)
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cache is the missing piece. `binary-trees`
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nodes escape into the tree, so scalar-replace can't remove them — residual GC
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pressure.
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## Running
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```sh
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bench/run.sh # full suite + JVM scorecard
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bench/run.sh fib # one benchmark, default size
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bench/run.sh fib 32 # one benchmark, custom size
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NO_JVM=1 bench/run.sh # jolt only (skip the JVM reference)
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```
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Needs Chez's kernel dev files (`libkernel.a` + `scheme.h`) and `cc` for the build,
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like `jolt build`; set `JOLT_CHEZ_CSV` to override the detected csv dir.
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## A/B against a change
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To measure a pass, run the suite on `main`, then on the branch, back to back
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(same machine, quiet). Each benchmark prints `runs: [...]` and `mean: N ms`;
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compare the means. A pass is worth landing when it moves a benchmark whose axis it
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targets, even if the ray tracer stays flat.
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