The AOT suite doesn't cover 64-bit integer arithmetic (Chez fixnums are 61-bit, so genuine 64-bit values are bignums) — the SplitMix PRNG behind test.check is the worst case. Add the measured jolt-vs-JVM numbers for the PRNG/mix-64 and the generator workload: the bitwise native-ops + var-cell caching took mix-64 from ~18x to ~3.2x JVM and the PRNG from ~30x to ~12x; the residual is the open-world generator dispatch/allocation and the bignum floor, not arithmetic.
6.6 KiB
jolt benchmark suite
Benchmarks that isolate the workload axes jolt's optimizing passes target. The
ray tracer (examples/ray-tracer) is float-compute-bound — its time is
irreducible algorithmic math (hit-testing + transcendentals), and devirt,
allocation removal, and type-proving all measured flat on it. So it can't
tell us whether those passes work. These benchmarks make each pass's target
workload the dominant cost.
Reference: the cross-language suites these draw from — Are We Fast Yet? (Marr et al., DLS '16) and the Computer Language Benchmarks Game. The benchmarks are portable Clojure, so they also run on JVM Clojure for an absolute reference.
Benchmarks
| Benchmark | Axis | Pass it exercises | Source |
|---|---|---|---|
binary-trees |
allocation / GC pressure (escaping short-lived records) | scalar-replace, escape analysis | CLBG |
dispatch |
polymorphic (megamorphic) protocol dispatch | devirt, inline-cache | AWFY-style |
mono-dispatch |
monomorphic protocol dispatch (devirt/inline-cache can fire) | devirt, inline-cache | AWFY-style |
collections |
persistent map/vector churn (HAMT / 32-way tries) | persistent structures, transients | CLBG k-nucleotide-style |
mandelbrot |
pure float compute (tight arith loops, no alloc/dispatch) | native arith, loop codegen | CLBG |
fib |
recursion: function-call + integer-arith overhead | native arith, small-fn inlining | CLBG |
What the ray tracer does not capture and these do: allocation as the bottleneck (~7% there), megamorphic and monomorphic dispatch (its dispatch is monomorphic and cheap), persistent-collection throughput (it uses fixed records, no collections in the hot loop), and isolated compute/call overhead.
Planned additions: Richards / DeltaBlue (heavier OO dispatch), NBody (float control with record state), k-nucleotide proper.
Holistic scorecard
bench/run.sh compiles each benchmark to an optimized AOT binary (joltc build --direct-link --opt) and times it against JVM Clojure running the same portable
source — the jolt/JVM scorecard. jolt's optimizing passes fire only in a build;
joltc run -m is unoptimized, so the harness always builds.
Indicative ratios (M-series, single isolated run — numbers are machine-specific, regenerate locally), ascending:
| benchmark | ratio | axis |
|---|---|---|
fib |
~0.6× | call + integer arith |
collections |
~3.5× | persistent map/vector churn |
mandelbrot |
~7.5× | pure float compute |
binary-trees |
~10× | escaping short-lived records (allocation/GC) |
dispatch |
~12× | megamorphic protocol dispatch |
mono-dispatch |
~15× | monomorphic protocol dispatch |
- Compute (~0.6–7.5×) is the substrate floor: Chez is a native-compiling AOT
Scheme, not a profiling JIT. With native arith + direct-linking + inlining jolt
is at parity here —
fibruns faster than JVM Clojure (no JIT warmup over a short run),collectionsis within ~3.5×, andmandelbrot(~7.5×) is the pure-tight-loop float ceiling that only native codegen moves further. - Dispatch & allocation (~10–15×) are the remaining architectural gaps, though
the type-proving / native-record / bare-field-read work has collapsed them by an
order of magnitude (
binary-trees~140×→~10×,mono-dispatch~330×→~15×). On a statically proven monomorphic receiver — which whole-program inference now gives for a record iterated out of a vector — devirt resolves the impl and a per-site inline cache holds it (resolved once, not per call), somono-dispatchis no longer worse than megamorphic. The remaining lever isdispatch: a megamorphic site has no static type, so it pays a full protocol-registry lookup every call where the JVM uses a polymorphic inline cache — a runtime (receiver-type-keyed) cache is the missing piece.binary-treesnodes escape into the tree, so scalar-replace can't remove them — residual GC pressure.
64-bit integer arithmetic & generators (test.check)
The AOT suite above is float-compute / dispatch / allocation bound; none of it
exercises 64-bit integer arithmetic, which Chez can't hold in a fixnum
(61-bit), so genuine 64-bit values are heap bignums. The SplitMix PRNG behind
clojure.test.check is the worst case — every rand-long is ~8 bignum ops. These
were measured in run mode (joltc run, where per-site var-cell caching is on;
the AOT build keeps it off) against JVM Clojure on the same portable source. The
first two rows are isolating microbenchmarks; the rest are real test.check
generators.
| workload | jolt | JVM | ratio | bound by |
|---|---|---|---|---|
SplitMix mix-64 (×100k) |
45ms | 14ms | ~3.2× | 64-bit integer arithmetic |
| deftype alloc + protocol dispatch (×100k) | 41ms | 5ms | ~8× | open-world dispatch |
raw split + rand-long (×20k) |
74ms | 6ms | ~12× | bignum 64-bit + dispatch |
gen/large-integer (×2k) |
108ms | 23ms | ~4.7× | arithmetic + rose-tree machinery |
(gen/vector gen/large-integer) (×500) |
1289ms | 88ms | ~14.6× | element gen + gen machinery |
Two no-C codegen levers collapsed the arithmetic half: emitting bit-and/
bit-or/bit-xor/bit-not as inlined Chez bitwise-* primitives (they had gone
through a var-deref'd variadic overlay), and caching the resolved var cell per
reference site (a name lookup was ~45ns/access). Together they took mix-64 from
~18× → ~3.2× JVM and the raw PRNG from ~30× → ~12×, and the generators ~1.6× each.
The residual gap is machinery, not arithmetic: the open-world generator deftype/protocol dispatch + rose-tree allocation (~8–10×) can't be devirtualized without static types, and the raw 64-bit ops bottom out at the Chez bignum floor (~20× a native long, substrate-inherent). A native SplitMix C/FFI shim would give the PRNG ~27× but is the only path that needs C.
Running
bench/run.sh # full suite + JVM scorecard
bench/run.sh fib # one benchmark, default size
bench/run.sh fib 32 # one benchmark, custom size
NO_JVM=1 bench/run.sh # jolt only (skip the JVM reference)
Needs Chez's kernel dev files (libkernel.a + scheme.h) and cc for the build,
like jolt build; set JOLT_CHEZ_CSV to override the detected csv dir.
A/B against a change
To measure a pass, run the suite on main, then on the branch, back to back
(same machine, quiet). Each benchmark prints runs: [...] and mean: N ms;
compare the means. A pass is worth landing when it moves a benchmark whose axis it
targets, even if the ray tracer stays flat.