Update baseline 11082026 by Quafadas · Pull Request #150 · Quafadas/vecxt

Quafadas · 2026-08-11T14:59:59Z

No description provided.

Commented out the matrix multiplication shape print statement.

github-actions · 2026-08-11T15:15:13Z

Bytecode audit (Tier 1) — ⚠️ no failures, 1 WARN

JDK 25.0.1 (major 25), OpenJDK 64-Bit Server VM

Vector lanes (DoubleVector.SPECIES_PREFERRED.length()): 8

threshold	value	provenance
`MaxTrivialSize`	6	discovered
`MaxInlineSize`	35	discovered
`FreqInlineSize`	325	discovered
`MaxInlineLevel`	15	discovered
`InlineSmallCode`	2500	discovered
`NodeCountInliningCutoff`	18000	assumed
`HugeMethodLimit`	8000	assumed

-XX:HugeMethodLimit= was rejected on the command line: a develop flag compiled out of this product build, so 8000 is taken from the HotSpot source and cannot be confirmed against the running JVM.

metric	now	baseline	delta
cheatsheet methods	57	—	—
total bytes	36556	36598	-0.1%
distinct library ops	204	205	-0.5%
bytes per op	179.2	178.5	+0.4%

severity	check	at	method	detail
WARN	C9	`bytecode/baseline.json`	`cheatsheet.scala`	the cheatsheet now invokes 204 distinct library operations, down from 205. A shrinking denominator loosens this check and unaudits whatever stopped being called

Annotated methods (182)

method	annotations	bytes	budget used	loop	at
`vecxt.floatarrays$.$minus$eq`	`@Thin`	26	74% of 35	no	`floatarrays.scala:736`
`vecxt.doublearrays$.$minus$eq`	`@Thin`	26	74% of 35	no	`doublearrays.scala:1031`
`vecxt.intarrays$.$plus`	`@Thin`	24	69% of 35	no	`intarrays.scala:546`
`vecxt.intarrays$.$minus`	`@Thin`	24	69% of 35	no	`intarrays.scala:399`
`vecxt.floatarrays$.$minus`	`@Thin`	24	69% of 35	no	`floatarrays.scala:725`
`vecxt.doublearrays$.$minus`	`@Thin`	24	69% of 35	no	`doublearrays.scala:1019`
`vecxt.floatarrays$.dot`	`@Thin`	23	66% of 35	no	`floatarrays.scala:651`
`vecxt.doublearrays$.dot`	`@Thin`	23	66% of 35	no	`doublearrays.scala:1004`
`vecxt.NDArrayFloatOps$.compareGeneral`	`@HotPath`	195	60% of 325	yes	`ndarrayFloatOps.scala:67`
`vecxt.NDArrayFloatOps$.binaryOpGeneral`	`@HotPath`	195	60% of 325	yes	`ndarrayFloatOps.scala:20`
`vecxt.NDArrayIntOps$.compareGeneral`	`@HotPath`	186	57% of 325	yes	`ndarrayIntOps.scala:67`
`vecxt.NDArrayIntOps$.binaryOpGeneral`	`@HotPath`	186	57% of 325	yes	`ndarrayIntOps.scala:19`
`vecxt.NDArrayDoubleOps$.compareGeneral`	`@HotPath`	186	57% of 325	yes	`ndarrayDoubleOps.scala:74`
`vecxt.NDArrayDoubleOps$.binaryOpGeneral`	`@HotPath`	186	57% of 325	yes	`ndarrayDoubleOps.scala:24`
`vecxt.doublearrays$.clamp$bang`	`@AllocFree` `@HotPath`	180	55% of 325	yes	`doublearrays.scala:898`
`vecxt.matrix$Layout.linearIndex`	`@Thin`	19	54% of 35	no	`matrix.scala:48`
`vecxt.floatarrays$.clamp$bang`	`@AllocFree` `@HotPath`	172	53% of 325	yes	`floatarrays.scala:419`
`vecxt.NDArrayFloatOps$.compareScalarGeneral`	`@HotPath`	165	51% of 325	yes	`ndarrayFloatOps.scala:94`
`vecxt.NDArrayFloatOps$.binaryOpInPlaceGeneral`	`@HotPath`	162	50% of 325	yes	`ndarrayFloatOps.scala:119`
`vecxt.NDArrayDoubleOps$.compareScalarGeneral`	`@HotPath`	157	48% of 325	yes	`ndarrayDoubleOps.scala:102`
`vecxt.NDArrayIntOps$.compareScalarGeneral`	`@HotPath`	156	48% of 325	yes	`ndarrayIntOps.scala:94`
`vecxt.NDArrayIntOps$.binaryOpInPlaceGeneral`	`@HotPath`	153	47% of 325	yes	`ndarrayIntOps.scala:119`
`vecxt.NDArrayDoubleOps$.binaryOpInPlaceGeneral`	`@HotPath`	153	47% of 325	yes	`ndarrayDoubleOps.scala:131`
`vecxt.NDArrayIntOps$.unaryOpGeneral`	`@HotPath`	152	47% of 325	yes	`ndarrayIntOps.scala:42`
`vecxt.NDArrayDoubleOps$.unaryOpGeneral`	`@HotPath`	152	47% of 325	yes	`ndarrayDoubleOps.scala:48`
`vecxt.intarrays$.$minus`	`@Thin`	16	46% of 35	no	`intarrays.scala:519`
`vecxt.floatarrays$.cumsum`	`@Thin`	15	43% of 35	no	`floatarrays.scala:695`
`vecxt.doublearrays$.cumsum`	`@Thin`	15	43% of 35	no	`doublearrays.scala:985`
`vecxt.doublearrays$.fillLinspace`	`@AllocFree` `@HotPath`	133	41% of 325	yes	`doublearrays.scala:34`
`vecxt.intarrays$.increments`	`@HotPath`	121	37% of 325	yes	`intarrays.scala:219`
`vecxt.ndarray$.mkNDArray`	`@Thin`	13	37% of 35	no	`ndarray.scala:188`
`vecxt.floatarrays$.norm`	`@Thin`	13	37% of 35	no	`floatarrays.scala:656`
`vecxt.doublearrays$.norm`	`@Thin`	13	37% of 35	no	`doublearrays.scala:1009`
`vecxt.doublearrays$.$plus`	`@AllocFree` `@HotPath`	116	36% of 325	yes	`doublearrays.scala:1065`
`vecxt.doublearrays$.$minus`	`@AllocFree` `@HotPath`	116	36% of 325	yes	`doublearrays.scala:1128`
`vecxt.doublearrays$.$div`	`@AllocFree` `@HotPath`	116	36% of 325	yes	`doublearrays.scala:1341`
`vecxt.doublearrays$.increments`	`@HotPath`	110	34% of 325	yes	`doublearrays.scala:397`
`vecxt.intarrays$.dot`	`@AllocFree` `@HotPath`	108	33% of 325	yes	`intarrays.scala:372`
`vecxt.doublearrays$.unary_$minus`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:172`
`vecxt.doublearrays$.tanh`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:365`
`vecxt.doublearrays$.tan`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:354`
`vecxt.doublearrays$.sqrt`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:317`
`vecxt.doublearrays$.sinh`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:339`
`vecxt.doublearrays$.sin`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:328`
`vecxt.doublearrays$.log1p`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:306`
`vecxt.doublearrays$.log10`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:295`
`vecxt.doublearrays$.log`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:284`
`vecxt.doublearrays$.expm1`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:273`
`vecxt.doublearrays$.exp`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:262`
`vecxt.doublearrays$.cosh`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:251`
`vecxt.doublearrays$.cos`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:240`
`vecxt.doublearrays$.cbrt`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:229`
`vecxt.doublearrays$.atan`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:218`
`vecxt.doublearrays$.asin`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:207`
`vecxt.doublearrays$.acos`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:196`
`vecxt.doublearrays$.abs`	`@HotPath`	108	33% of 325	yes	`doublearrays.scala:184`
`vecxt.intarrays$.$less`	`@HotPath`	106	33% of 325	yes	`intarrays.scala:48`
`vecxt.intarrays$.$less$eq`	`@HotPath`	106	33% of 325	yes	`intarrays.scala:52`
`vecxt.intarrays$.$greater`	`@HotPath`	106	33% of 325	yes	`intarrays.scala:56`
`vecxt.intarrays$.$greater$eq`	`@HotPath`	106	33% of 325	yes	`intarrays.scala:60`
`vecxt.intarrays$.$eq$colon$eq`	`@HotPath`	106	33% of 325	yes	`intarrays.scala:40`
`vecxt.intarrays$.$bang$colon$eq`	`@HotPath`	106	33% of 325	yes	`intarrays.scala:44`
`vecxt.floatarrays$.unary_$minus`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:116`
`vecxt.floatarrays$.tanh`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:305`
`vecxt.floatarrays$.tan`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:294`
`vecxt.floatarrays$.sqrt`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:261`
`vecxt.floatarrays$.sinh`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:283`
`vecxt.floatarrays$.sin`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:272`
`vecxt.floatarrays$.log1p`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:250`
`vecxt.floatarrays$.log10`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:239`
`vecxt.floatarrays$.log`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:228`
`vecxt.floatarrays$.expm1`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:217`
`vecxt.floatarrays$.exp`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:206`
`vecxt.floatarrays$.cosh`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:195`
`vecxt.floatarrays$.cos`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:184`
`vecxt.floatarrays$.cbrt`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:173`
`vecxt.floatarrays$.atan`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:162`
`vecxt.floatarrays$.asin`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:151`
`vecxt.floatarrays$.acos`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:140`
`vecxt.floatarrays$.abs`	`@HotPath`	104	32% of 325	yes	`floatarrays.scala:128`
`vecxt.intarrays$.mean`	`@Thin`	11	31% of 35	no	`intarrays.scala:287`
`vecxt.doublearrays$.sumSIMD`	`@AllocFree` `@HotPath`	102	31% of 325	yes	`doublearrays.scala:703`
`vecxt.doublearrays$.tanh$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.tan$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.sqrt$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.sinh$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.sin$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.log1p$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.log10$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.log$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.expm1$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.exp$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.cosh$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.cos$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.cbrt$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.atan$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.asin$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.acos$bang`	`@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.abs$bang`	`@AllocFree` `@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.doublearrays$.$minus$bang`	`@AllocFree` `@HotPath`	98	30% of 325	yes	`doublearrays.scala:151`
`vecxt.floatarrays$.increments`	`@HotPath`	97	30% of 325	yes	`floatarrays.scala:660`
`vecxt.doublearrays$.$times$times$bang`	`@HotPath`	95	29% of 325	yes	`doublearrays.scala:372`
`vecxt.intarrays$.$less`	`@HotPath`	94	29% of 325	yes	`intarrays.scala:139`
`vecxt.intarrays$.$less$eq`	`@HotPath`	94	29% of 325	yes	`intarrays.scala:143`
`vecxt.intarrays$.$greater`	`@HotPath`	94	29% of 325	yes	`intarrays.scala:147`
`vecxt.intarrays$.$greater$eq`	`@HotPath`	94	29% of 325	yes	`intarrays.scala:151`
`vecxt.intarrays$.$eq$colon$eq`	`@HotPath`	94	29% of 325	yes	`intarrays.scala:131`
`vecxt.intarrays$.$bang$colon$eq`	`@HotPath`	94	29% of 325	yes	`intarrays.scala:135`
`vecxt.floatarrays$.tanh$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.tan$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.sqrt$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.sinh$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.sin$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.log1p$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.log10$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.log$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.expm1$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.exp$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.cosh$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.cos$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.cbrt$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.atan$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.asin$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.acos$bang`	`@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.abs$bang`	`@AllocFree` `@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.floatarrays$.$minus$bang`	`@AllocFree` `@HotPath`	93	29% of 325	yes	`floatarrays.scala:96`
`vecxt.intarrays$.variance`	`@Thin`	10	29% of 35	no	`intarrays.scala:304`
`vecxt.intarrays$.std`	`@Thin`	10	29% of 35	no	`intarrays.scala:361`
`vecxt.doublearrays$.variance`	`@AllocFree` `@Thin`	10	29% of 35	no	`doublearrays.scala:541`
`vecxt.doublearrays$.$plus$eq`	`@AllocFree` `@HotPath`	90	28% of 325	yes	`doublearrays.scala:1087`
`vecxt.doublearrays$.$minus$eq`	`@AllocFree` `@HotPath`	90	28% of 325	yes	`doublearrays.scala:1175`
`vecxt.doublearrays$.$times$eq`	`@AllocFree` `@HotPath`	88	27% of 325	yes	`doublearrays.scala:1250`
`vecxt.doublearrays$.productSIMD`	`@AllocFree` `@HotPath`	86	26% of 325	yes	`doublearrays.scala:726`
`vecxt.floatarrays$.$times$times$bang`	`@HotPath`	85	26% of 325	yes	`floatarrays.scala:316`
`vecxt.doublearrays$.sumSIMD`	`@AllocFree` `@HotPath`	85	26% of 325	yes	`doublearrays.scala:677`
`vecxt.doublearrays$.fma$bang`	`@AllocFree` `@HotPath`	85	26% of 325	yes	`doublearrays.scala:1150`
`vecxt.intarrays$.$plus$eq`	`@AllocFree` `@HotPath`	84	26% of 325	yes	`intarrays.scala:555`
`vecxt.intarrays$.$minus$eq`	`@AllocFree` `@HotPath`	84	26% of 325	yes	`intarrays.scala:527`
`vecxt.floatarrays$.$times$eq`	`@AllocFree` `@HotPath`	84	26% of 325	yes	`floatarrays.scala:893`
`vecxt.floatarrays$.$plus$eq`	`@AllocFree` `@HotPath`	84	26% of 325	yes	`floatarrays.scala:791`
`vecxt.floatarrays$.$minus$eq`	`@AllocFree` `@HotPath`	84	26% of 325	yes	`floatarrays.scala:831`
`vecxt.ndarrayOps.expandDims`	`@Thin`	9	26% of 35	no	`ndarrayOps.scala`
`vecxt.intarrays.stdDev`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.meanAndVariance`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.lte`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.lte`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.lt`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.lt`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.gte`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.gte`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.gt`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays.gt`	`@Thin`	9	26% of 35	no	`intarrays.scala`
`vecxt.intarrays$.variance`	`@Thin`	9	26% of 35	no	`intarrays.scala:291`
`vecxt.intarrays$.stdDev`	`@Thin`	9	26% of 35	no	`intarrays.scala:364`
`vecxt.intarrays$.std`	`@Thin`	9	26% of 35	no	`intarrays.scala:357`
`vecxt.intarrays$.meanAndVariance`	`@Thin`	9	26% of 35	no	`intarrays.scala:308`
`vecxt.doublearrays.meanAndVariance`	`@Thin`	9	26% of 35	no	`doublearrays.scala`
`vecxt.doublearrays$.meanAndVariance`	`@Thin`	9	26% of 35	no	`doublearrays.scala:555`
`vecxt.intarrays$.minSIMD`	`@AllocFree` `@HotPath`	82	25% of 325	yes	`intarrays.scala:575`
`vecxt.intarrays$.maxSIMD`	`@AllocFree` `@HotPath`	82	25% of 325	yes	`intarrays.scala:595`
`vecxt.floatarrays$.productSIMD`	`@AllocFree` `@HotPath`	82	25% of 325	yes	`floatarrays.scala:539`
`vecxt.intarrays$.sumSIMD`	`@AllocFree` `@HotPath`	81	25% of 325	yes	`intarrays.scala:265`
`vecxt.floatarrays$.sumSIMD`	`@AllocFree` `@HotPath`	81	25% of 325	yes	`floatarrays.scala:518`
`vecxt.floatarrays$.fma$bang`	`@AllocFree` `@HotPath`	80	25% of 325	yes	`floatarrays.scala:342`
`vecxt.floatarrays$.$times$eq`	`@AllocFree` `@HotPath`	78	24% of 325	yes	`floatarrays.scala:945`
`vecxt.ndarray.shapeArray`	`@Thin`	8	23% of 35	no	`ndarray.scala`
`vecxt.matrix$Matrix.rows`	`@Thin`	8	23% of 35	no	`matrix.scala:195`
`vecxt.matrix$Matrix.rowStride`	`@Thin`	8	23% of 35	no	`matrix.scala:201`
`vecxt.matrix$Matrix.offset`	`@Thin`	8	23% of 35	no	`matrix.scala:207`
`vecxt.matrix$Matrix.numel`	`@Thin`	8	23% of 35	no	`matrix.scala:210`
`vecxt.matrix$Matrix.isDenseRowMajor`	`@Thin`	8	23% of 35	no	`matrix.scala:216`
`vecxt.matrix$Matrix.isDenseColMajor`	`@Thin`	8	23% of 35	no	`matrix.scala:213`
`vecxt.matrix$Matrix.hasSimpleContiguousMemoryLayout`	`@Thin`	8	23% of 35	no	`matrix.scala:228`
`vecxt.matrix$Matrix.cols`	`@Thin`	8	23% of 35	no	`matrix.scala:198`
`vecxt.matrix$Matrix.colStride`	`@Thin`	8	23% of 35	no	`matrix.scala:204`
`vecxt.intarrays$.countsToIdx`	`@HotPath`	70	22% of 325	yes	`intarrays.scala:244`
`vecxt.intarrays$.$minus$eq`	`@AllocFree` `@HotPath`	67	21% of 325	yes	`intarrays.scala:408`
`vecxt.IntArraysX$.select`	`@HotPath`	44	14% of 325	yes	`intarray.scala:74`
`vecxt.IntArraysX$.contiguous`	`@HotPath`	39	12% of 325	yes	`intarray.scala:111`
`vecxt.floatarrays$.cumsum$bang`	`@AllocFree` `@HotPath`	27	8% of 325	yes	`floatarrays.scala:686`
`vecxt.doublearrays$.cumsum$bang`	`@AllocFree` `@HotPath`	27	8% of 325	yes	`doublearrays.scala:976`
`vecxt.floatarrays$.$plus$eq`	`@AllocFree` `@HotPath`	24	7% of 325	no	`floatarrays.scala:750`

Method sizes

band	methods
<= 6 (trivial, always inlined)	1435
7-35 (inlinable cold)	3665
36-325 (inlinable when hot)	673
326-8000 (not inlined)	112
> 8000 (NEVER JIT COMPILED)	0

bytes	method	module	at
4635	`CheatsheetTest$.matrixRangeSlicing`	experiments	`cheatsheet.scala:118`
3801	`CheatsheetTest$.ndArrayInt`	experiments	`cheatsheet.scala:416`
3779	`CheatsheetTest$.ndArrayBoolean`	experiments	`cheatsheet.scala:430`
3143	`CheatsheetTest$.matrixReverseSlicing`	experiments	`cheatsheet.scala:125`
3061	`CheatsheetTest$.ndArrayFloat`	experiments	`cheatsheet.scala:395`
3015	`CheatsheetTest$.ndArrayFloatReductions`	experiments	`cheatsheet.scala:405`
2500	`vecxt_re.Tower.show`	vecxt_re	`Tower.scala:63`
2483	`CheatsheetTest$.matrixCreation`	experiments	`cheatsheet.scala:72`
2120	`CheatsheetTest$.matrixOps`	experiments	`cheatsheet.scala:167`
1568	`vecxt.ndarrayOps$.apply`	vecxt	`ndarrayOps.scala:452`
1225	`vecxt.JvmFloatMatrix$.floatmatrixSubVector`	vecxt	`floatmatrix.scala:324`
1200	`CheatsheetTest$.arrayManipulation`	experiments	`cheatsheet.scala:305`
1189	`vecxt.JvmDoubleMatrix$.$plus$eq`	vecxt	`doublematrix.scala:220`
1165	`vecxt.JvmFloatMatrix$.floatmatrixAddVectorInPlace`	vecxt	`floatmatrix.scala:242`
1165	`vecxt.JvmFloatMatrix$.floatmatrixSubVectorInPlace`	vecxt	`floatmatrix.scala:342`
1043	`vecxt.JvmDoubleMatrix$.$plus$eq`	vecxt	`doublematrix.scala:302`
1028	`vecxt.JvmFloatMatrix$.floatmatrixAddScalarInPlace`	vecxt	`floatmatrix.scala:418`
1028	`vecxt.JvmFloatMatrix$.floatmatrixSubScalarInPlace`	vecxt	`floatmatrix.scala:490`
969	`vecxt_re.Scenarr$.combine`	vecxt_re	`scenarr.scala:160`
908	`vecxt.Svd$.svd`	vecxt	`svd.scala:135`
902	`vecxt.Svd$.pinv`	vecxt	`svd.scala:42`
896	`vecxt_re.NegativeBinomial$.volweightedMle`	vecxt_re	`NegativeBinomial.scala:281`
878	`vecxt_re.NegativeBinomial$.mle`	vecxt_re	`NegativeBinomial.scala:151`
822	`vecxt.DoubleMatrix$.hadamard`	vecxt	`doublematrix.scala:263`
816	`vecxt_re.Layer.equals`	vecxt_re	`Layer.scala:21`

Proposed baseline

{
  "jdkMajor": 25,
  "c9": { "totalBytes": 36556, "distinctOps": 204 },
  "annotated": {
    "vecxt.IntArraysX$.contiguous([I)Z": 39,
    "vecxt.IntArraysX$.select([I[I)[I": 44,
    "vecxt.NDArrayDoubleOps$.binaryOpGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayDoubleOps$.binaryOpInPlaceGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)V": 153,
    "vecxt.NDArrayDoubleOps$.compareGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayDoubleOps$.compareScalarGeneral(Lvecxt/ndarray$NDArray;DLscala/Function2;)Lvecxt/ndarray$NDArray;": 157,
    "vecxt.NDArrayDoubleOps$.unaryOpGeneral(Lvecxt/ndarray$NDArray;Lscala/Function1;)Lvecxt/ndarray$NDArray;": 152,
    "vecxt.NDArrayFloatOps$.binaryOpGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 195,
    "vecxt.NDArrayFloatOps$.binaryOpInPlaceGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)V": 162,
    "vecxt.NDArrayFloatOps$.compareGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 195,
    "vecxt.NDArrayFloatOps$.compareScalarGeneral(Lvecxt/ndarray$NDArray;FLscala/Function2;)Lvecxt/ndarray$NDArray;": 165,
    "vecxt.NDArrayIntOps$.binaryOpGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayIntOps$.binaryOpInPlaceGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)V": 153,
    "vecxt.NDArrayIntOps$.compareGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayIntOps$.compareScalarGeneral(Lvecxt/ndarray$NDArray;ILscala/Function2;)Lvecxt/ndarray$NDArray;": 156,
    "vecxt.NDArrayIntOps$.unaryOpGeneral(Lvecxt/ndarray$NDArray;Lscala/Function1;)Lvecxt/ndarray$NDArray;": 152,
    "vecxt.doublearrays$.$div([DDII[DI)V": 116,
    "vecxt.doublearrays$.$minus$bang([D)V": 98,
    "vecxt.doublearrays$.$minus$eq([DD)V": 90,
    "vecxt.doublearrays$.$minus$eq([D[D)V": 26,
    "vecxt.doublearrays$.$minus([DDII[DI)V": 116,
    "vecxt.doublearrays$.$minus([D[D)[D": 24,
    "vecxt.doublearrays$.$plus$eq([DD)V": 90,
    "vecxt.doublearrays$.$plus([DDII[DI)V": 116,
    "vecxt.doublearrays$.$times$eq([D[D)V": 88,
    "vecxt.doublearrays$.$times$times$bang([DD)V": 95,
    "vecxt.doublearrays$.abs$bang([D)V": 98,
    "vecxt.doublearrays$.abs([D)[D": 108,
    "vecxt.doublearrays$.acos$bang([D)V": 98,
    "vecxt.doublearrays$.acos([D)[D": 108,
    "vecxt.doublearrays$.asin$bang([D)V": 98,
    "vecxt.doublearrays$.asin([D)[D": 108,
    "vecxt.doublearrays$.atan$bang([D)V": 98,
    "vecxt.doublearrays$.atan([D)[D": 108,
    "vecxt.doublearrays$.cbrt$bang([D)V": 98,
    "vecxt.doublearrays$.cbrt([D)[D": 108,
    "vecxt.doublearrays$.clamp$bang([DDD)V": 180,
    "vecxt.doublearrays$.cos$bang([D)V": 98,
    "vecxt.doublearrays$.cos([D)[D": 108,
    "vecxt.doublearrays$.cosh$bang([D)V": 98,
    "vecxt.doublearrays$.cosh([D)[D": 108,
    "vecxt.doublearrays$.cumsum$bang([D)V": 27,
    "vecxt.doublearrays$.cumsum([D)[D": 15,
    "vecxt.doublearrays$.dot([D[D)D": 23,
    "vecxt.doublearrays$.exp$bang([D)V": 98,
    "vecxt.doublearrays$.exp([D)[D": 108,
    "vecxt.doublearrays$.expm1$bang([D)V": 98,
    "vecxt.doublearrays$.expm1([D)[D": 108,
    "vecxt.doublearrays$.fillLinspace([DDD)V": 133,
    "vecxt.doublearrays$.fma$bang([DDD)V": 85,
    "vecxt.doublearrays$.increments([D)[D": 110,
    "vecxt.doublearrays$.log$bang([D)V": 98,
    "vecxt.doublearrays$.log([D)[D": 108,
    "vecxt.doublearrays$.log10$bang([D)V": 98,
    "vecxt.doublearrays$.log10([D)[D": 108,
    "vecxt.doublearrays$.log1p$bang([D)V": 98,
    "vecxt.doublearrays$.log1p([D)[D": 108,
    "vecxt.doublearrays$.meanAndVariance([D)Lvecxt/MeanAndVariance;": 9,
    "vecxt.doublearrays$.norm([D)D": 13,
    "vecxt.doublearrays$.productSIMD([D)D": 86,
    "vecxt.doublearrays$.sin$bang([D)V": 98,
    "vecxt.doublearrays$.sin([D)[D": 108,
    "vecxt.doublearrays$.sinh$bang([D)V": 98,
    "vecxt.doublearrays$.sinh([D)[D": 108,
    "vecxt.doublearrays$.sqrt$bang([D)V": 98,
    "vecxt.doublearrays$.sqrt([D)[D": 108,
    "vecxt.doublearrays$.sumSIMD([D)D": 85,
    "vecxt.doublearrays$.sumSIMD([DII)D": 102,
    "vecxt.doublearrays$.tan$bang([D)V": 98,
    "vecxt.doublearrays$.tan([D)[D": 108,
    "vecxt.doublearrays$.tanh$bang([D)V": 98,
    "vecxt.doublearrays$.tanh([D)[D": 108,
    "vecxt.doublearrays$.unary_$minus([D)[D": 108,
    "vecxt.doublearrays$.variance([DLvecxt/VarianceMode;)D": 10,
    "vecxt.doublearrays.meanAndVariance([DLvecxt/VarianceMode;)Lvecxt/MeanAndVariance;": 9,
    "vecxt.floatarrays$.$minus$bang([F)V": 93,
    "vecxt.floatarrays$.$minus$eq([FF)V": 84,
    "vecxt.floatarrays$.$minus$eq([F[F)V": 26,
    "vecxt.floatarrays$.$minus([F[F)[F": 24,
    "vecxt.floatarrays$.$plus$eq([FF)V": 84,
    "vecxt.floatarrays$.$plus$eq([F[F)V": 24,
    "vecxt.floatarrays$.$times$eq([FF)V": 78,
    "vecxt.floatarrays$.$times$eq([F[F)V": 84,
    "vecxt.floatarrays$.$times$times$bang([FF)V": 85,
    "vecxt.floatarrays$.abs$bang([F)V": 93,
    "vecxt.floatarrays$.abs([F)[F": 104,
    "vecxt.floatarrays$.acos$bang([F)V": 93,
    "vecxt.floatarrays$.acos([F)[F": 104,
    "vecxt.floatarrays$.asin$bang([F)V": 93,
    "vecxt.floatarrays$.asin([F)[F": 104,
    "vecxt.floatarrays$.atan$bang([F)V": 93,
    "vecxt.floatarrays$.atan([F)[F": 104,
    "vecxt.floatarrays$.cbrt$bang([F)V": 93,
    "vecxt.floatarrays$.cbrt([F)[F": 104,
    "vecxt.floatarrays$.clamp$bang([FFF)V": 172,
    "vecxt.floatarrays$.cos$bang([F)V": 93,
    "vecxt.floatarrays$.cos([F)[F": 104,
    "vecxt.floatarrays$.cosh$bang([F)V": 93,
    "vecxt.floatarrays$.cosh([F)[F": 104,
    "vecxt.floatarrays$.cumsum$bang([F)V": 27,
    "vecxt.floatarrays$.cumsum([F)[F": 15,
    "vecxt.floatarrays$.dot([F[F)F": 23,
    "vecxt.floatarrays$.exp$bang([F)V": 93,
    "vecxt.floatarrays$.exp([F)[F": 104,
    "vecxt.floatarrays$.expm1$bang([F)V": 93,
    "vecxt.floatarrays$.expm1([F)[F": 104,
    "vecxt.floatarrays$.fma$bang([FFF)V": 80,
    "vecxt.floatarrays$.increments([F)[F": 97,
    "vecxt.floatarrays$.log$bang([F)V": 93,
    "vecxt.floatarrays$.log([F)[F": 104,
    "vecxt.floatarrays$.log10$bang([F)V": 93,
    "vecxt.floatarrays$.log10([F)[F": 104,
    "vecxt.floatarrays$.log1p$bang([F)V": 93,
    "vecxt.floatarrays$.log1p([F)[F": 104,
    "vecxt.floatarrays$.norm([F)F": 13,
    "vecxt.floatarrays$.productSIMD([F)F": 82,
    "vecxt.floatarrays$.sin$bang([F)V": 93,
    "vecxt.floatarrays$.sin([F)[F": 104,
    "vecxt.floatarrays$.sinh$bang([F)V": 93,
    "vecxt.floatarrays$.sinh([F)[F": 104,
    "vecxt.floatarrays$.sqrt$bang([F)V": 93,
    "vecxt.floatarrays$.sqrt([F)[F": 104,
    "vecxt.floatarrays$.sumSIMD([F)F": 81,
    "vecxt.floatarrays$.tan$bang([F)V": 93,
    "vecxt.floatarrays$.tan([F)[F": 104,
    "vecxt.floatarrays$.tanh$bang([F)V": 93,
    "vecxt.floatarrays$.tanh([F)[F": 104,
    "vecxt.floatarrays$.unary_$minus([F)[F": 104,
    "vecxt.intarrays$.$bang$colon$eq([II)[Z": 94,
    "vecxt.intarrays$.$bang$colon$eq([I[I)[Z": 106,
    "vecxt.intarrays$.$eq$colon$eq([II)[Z": 94,
    "vecxt.intarrays$.$eq$colon$eq([I[I)[Z": 106,
    "vecxt.intarrays$.$greater$eq([II)[Z": 94,
    "vecxt.intarrays$.$greater$eq([I[I)[Z": 106,
    "vecxt.intarrays$.$greater([II)[Z": 94,
    "vecxt.intarrays$.$greater([I[I)[Z": 106,
    "vecxt.intarrays$.$less$eq([II)[Z": 94,
    "vecxt.intarrays$.$less$eq([I[I)[Z": 106,
    "vecxt.intarrays$.$less([II)[Z": 94,
    "vecxt.intarrays$.$less([I[I)[Z": 106,
    "vecxt.intarrays$.$minus$eq([II)V": 67,
    "vecxt.intarrays$.$minus$eq([I[I)V": 84,
    "vecxt.intarrays$.$minus([II)[I": 16,
    "vecxt.intarrays$.$minus([I[I)[I": 24,
    "vecxt.intarrays$.$plus$eq([I[I)V": 84,
    "vecxt.intarrays$.$plus([I[I)[I": 24,
    "vecxt.intarrays$.countsToIdx([I)[I": 70,
    "vecxt.intarrays$.dot([I[I)I": 108,
    "vecxt.intarrays$.increments([I)[I": 121,
    "vecxt.intarrays$.maxSIMD([I)I": 82,
    "vecxt.intarrays$.mean([I)D": 11,
    "vecxt.intarrays$.meanAndVariance([I)Lvecxt/MeanAndVariance;": 9,
    "vecxt.intarrays$.minSIMD([I)I": 82,
    "vecxt.intarrays$.std([I)D": 9,
    "vecxt.intarrays$.std([ILvecxt/VarianceMode;)D": 10,
    "vecxt.intarrays$.stdDev([I)D": 9,
    "vecxt.intarrays$.sumSIMD([I)I": 81,
    "vecxt.intarrays$.variance([I)D": 9,
    "vecxt.intarrays$.variance([ILvecxt/VarianceMode;)D": 10,
    "vecxt.intarrays.gt([II)[Z": 9,
    "vecxt.intarrays.gt([I[I)[Z": 9,
    "vecxt.intarrays.gte([II)[Z": 9,
    "vecxt.intarrays.gte([I[I)[Z": 9,
    "vecxt.intarrays.lt([II)[Z": 9,
    "vecxt.intarrays.lt([I[I)[Z": 9,
    "vecxt.intarrays.lte([II)[Z": 9,
    "vecxt.intarrays.lte([I[I)[Z": 9,
    "vecxt.intarrays.meanAndVariance([ILvecxt/VarianceMode;)Lvecxt/MeanAndVariance;": 9,
    "vecxt.intarrays.stdDev([ILvecxt/VarianceMode;)D": 9,
    "vecxt.matrix$Layout.linearIndex(II)I": 19,
    "vecxt.matrix$Matrix.colStride()I": 8,
    "vecxt.matrix$Matrix.cols()I": 8,
    "vecxt.matrix$Matrix.hasSimpleContiguousMemoryLayout()Z": 8,
    "vecxt.matrix$Matrix.isDenseColMajor()Z": 8,
    "vecxt.matrix$Matrix.isDenseRowMajor()Z": 8,
    "vecxt.matrix$Matrix.numel()I": 8,
    "vecxt.matrix$Matrix.offset()I": 8,
    "vecxt.matrix$Matrix.rowStride()I": 8,
    "vecxt.matrix$Matrix.rows()I": 8,
    "vecxt.ndarray$.mkNDArray(Ljava/lang/Object;[I[II)Lvecxt/ndarray$NDArray;": 13,
    "vecxt.ndarray.shapeArray(Lvecxt/ndarray$NDArray;)[I": 8,
    "vecxt.ndarrayOps.expandDims(Lvecxt/ndarray$NDArray;I)Lvecxt/ndarray$NDArray;": 9
  }
}

Quafadas and others added 5 commits August 11, 2026 14:50

update baseline

aa53e32

update ??? useages

45c3ca0

.

2281d0f

[autofix.ci] apply automated fixes

847aef8

Comment out matmul shape print statement

a5b8ad7

Commented out the matrix multiplication shape print statement.

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Update baseline 11082026 - #150

Update baseline 11082026#150
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Bytecode audit (Tier 1) — ⚠️ no failures, 1 WARN

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