Note Diffing the performance result against the published result from main branch. Unchanged benchmarks are omitted.

Map

	binary_size	generate 1m	max mem	batch_get 50	batch_put 50	batch_remove 50	upgrade
hashmap	160_407 ($\textcolor{red}{0.12\%}$)	8_550_261_900 ($\textcolor{red}{22.43\%}$)	61_987_852	349_808 ($\textcolor{red}{21.18\%}$)	6_641_222_848 ($\textcolor{red}{19.95\%}$)	377_790 ($\textcolor{red}{21.79\%}$)	11_273_695_870 ($\textcolor{red}{23.50\%}$)
triemap	163_606 ($\textcolor{red}{0.08\%}$)	15_268_684_428 ($\textcolor{red}{33.19\%}$)	74_216_172	301_412 ($\textcolor{red}{35.21\%}$)	737_508 ($\textcolor{red}{34.23\%}$)	722_627 ($\textcolor{red}{33.77\%}$)	17_302_961_961 ($\textcolor{red}{32.33\%}$)
rbtree	158_225 ($\textcolor{red}{0.05\%}$)	7_665_886_603 ($\textcolor{red}{28.21\%}$)	57_996_060	115_637 ($\textcolor{red}{30.07\%}$)	346_274 ($\textcolor{red}{28.93\%}$)	370_932 ($\textcolor{red}{33.26\%}$)	7_231_296_002 ($\textcolor{red}{25.28\%}$)
splay	160_055 ($\textcolor{red}{0.06\%}$)	15_388_999_493 ($\textcolor{red}{33.03\%}$)	53_995_996	738_550 ($\textcolor{red}{33.79\%}$)	777_813 ($\textcolor{red}{33.70\%}$)	1_077_553 ($\textcolor{red}{32.98\%}$)	4_832_227_514 ($\textcolor{red}{29.81\%}$)
btree	188_004 ($\textcolor{red}{0.06\%}$)	11_040_703_048 ($\textcolor{red}{34.25\%}$)	31_104_012	376_209 ($\textcolor{red}{35.55\%}$)	519_468 ($\textcolor{red}{35.22\%}$)	577_253 ($\textcolor{red}{34.54\%}$)	3_162_844_776 ($\textcolor{red}{25.61\%}$)
zhenya_hashmap	160_784 ($\textcolor{red}{0.17\%}$)	2_838_455_412 ($\textcolor{red}{28.93\%}$)	22_773_100	66_353 ($\textcolor{red}{36.45\%}$)	84_294 ($\textcolor{red}{36.31\%}$)	96_614 ($\textcolor{red}{36.32\%}$)	3_353_572_476 ($\textcolor{red}{24.42\%}$)
btreemap_rs	478_653 ($\textcolor{green}{-0.03\%}$)	1_797_168_137 ($\textcolor{red}{8.81\%}$)	27_590_656	75_573 ($\textcolor{red}{13.03\%}$)	125_437 ($\textcolor{red}{11.52\%}$)	86_323 ($\textcolor{red}{13.23\%}$)	2_941_065_080 ($\textcolor{red}{10.53\%}$)
imrc_hashmap_rs	482_783 ($\textcolor{green}{-0.03\%}$)	2_584_652_919 ($\textcolor{red}{8.01\%}$)	244_973_568	38_439 ($\textcolor{red}{17.32\%}$)	179_288 ($\textcolor{red}{9.83\%}$)	115_588 ($\textcolor{red}{17.47\%}$)	5_796_576_276 ($\textcolor{red}{11.65\%}$)
hashmap_rs	469_075 ($\textcolor{green}{-0.04\%}$)	433_765_793 ($\textcolor{red}{7.56\%}$)	73_138_176	21_856 ($\textcolor{red}{29.70\%}$)	26_958 ($\textcolor{red}{24.35\%}$)	25_223 ($\textcolor{red}{24.48\%}$)	1_293_479_144 ($\textcolor{red}{12.98\%}$)

Priority queue

	binary_size	heapify 1m	max mem	pop_min 50	put 50	pop_min 50.1	upgrade
heap	147_908 ($\textcolor{red}{0.18\%}$)	6_393_606_585 ($\textcolor{red}{36.48\%}$)	29_995_956	701_835 ($\textcolor{red}{37.21\%}$)	258_841 ($\textcolor{red}{38.81\%}$)	668_731 ($\textcolor{red}{37.25\%}$)	3_337_783_210 ($\textcolor{red}{25.69\%}$)
heap_rs	462_827 ($\textcolor{green}{-0.03\%}$)	138_669_875 ($\textcolor{red}{14.04\%}$)	18_284_544	57_564 ($\textcolor{red}{11.43\%}$)	23_346 ($\textcolor{red}{27.96\%}$)	57_696 ($\textcolor{red}{11.38\%}$)	511_961_256 ($\textcolor{red}{16.16\%}$)

Growable array

	binary_size	generate 5k	max mem	batch_get 500	batch_put 500	batch_remove 500	upgrade
buffer	151_225 ($\textcolor{red}{0.15\%}$)	2_811_683 ($\textcolor{red}{35.01\%}$)	65_644	109_527 ($\textcolor{red}{49.85\%}$)	884_994 ($\textcolor{red}{31.79\%}$)	178_027 ($\textcolor{red}{39.53\%}$)	3_206_695 ($\textcolor{red}{29.58\%}$)
vector	152_845 ($\textcolor{red}{0.19\%}$)	2_228_708 ($\textcolor{red}{40.32\%}$)	24_580	146_173 ($\textcolor{red}{38.96\%}$)	212_398 ($\textcolor{red}{41.66\%}$)	203_951 ($\textcolor{red}{37.72\%}$)	4_810_168 ($\textcolor{red}{25.12\%}$)
vec_rs	460_616 ($\textcolor{green}{-0.03\%}$)	289_093 ($\textcolor{red}{8.81\%}$)	1_310_720	17_300 ($\textcolor{red}{32.93\%}$)	30_623 ($\textcolor{red}{20.74\%}$)	25_759 ($\textcolor{red}{21.24\%}$)	3_171_850 ($\textcolor{red}{15.60\%}$)

Stable structures

	binary_size	generate 50k	max mem	batch_get 50	batch_put 50	batch_remove 50	upgrade
btreemap_rs	478_653 ($\textcolor{green}{-0.03\%}$)	76_392_041 ($\textcolor{red}{9.09\%}$)	2_555_904	65_131 ($\textcolor{red}{13.90\%}$)	97_327 ($\textcolor{red}{12.52\%}$)	85_332 ($\textcolor{red}{13.31\%}$)	126_467_483 ($\textcolor{red}{11.09\%}$)
btreemap_stable_rs	488_655 ($\textcolor{green}{-0.04\%}$)	5_255_681_694 ($\textcolor{red}{14.05\%}$)	2_031_616	3_167_281 ($\textcolor{red}{13.99\%}$)	5_784_578 ($\textcolor{red}{14.08\%}$)	9_888_420 ($\textcolor{red}{14.48\%}$)	731_129 ($\textcolor{red}{11.91\%}$)
heap_rs	462_827 ($\textcolor{green}{-0.03\%}$)	7_001_771 ($\textcolor{red}{14.04\%}$)	2_293_760	50_073 ($\textcolor{red}{12.87\%}$)	23_594 ($\textcolor{red}{27.69\%}$)	50_045 ($\textcolor{red}{12.85\%}$)	26_819_762 ($\textcolor{red}{15.86\%}$)
heap_stable_rs	450_750 ($\textcolor{green}{-0.04\%}$)	319_633_530 ($\textcolor{red}{14.86\%}$)	458_752	2_674_744 ($\textcolor{red}{14.80\%}$)	278_372 ($\textcolor{red}{15.87\%}$)	2_654_546 ($\textcolor{red}{14.80\%}$)	731_276 ($\textcolor{red}{11.91\%}$)
vec_rs	460_616 ($\textcolor{green}{-0.03\%}$)	3_079_437 ($\textcolor{red}{7.41\%}$)	2_228_224	17_300 ($\textcolor{red}{32.93\%}$)	18_473 ($\textcolor{red}{30.89\%}$)	18_000 ($\textcolor{red}{31.29\%}$)	24_772_373 ($\textcolor{red}{16.58\%}$)
vec_stable_rs	448_692 ($\textcolor{green}{-0.05\%}$)	75_145_339 ($\textcolor{red}{15.28\%}$)	458_752	70_326 ($\textcolor{red}{18.82\%}$)	91_522 ($\textcolor{red}{18.27\%}$)	93_718 ($\textcolor{red}{17.77\%}$)	731_289 ($\textcolor{red}{11.91\%}$)

Statistics

binary_size: 0.03% [-0.00%, 0.07%]
max_mem: no change
cycles: 23.45% [21.73%, 25.17%]

SHA-2

	binary_size	SHA-256	SHA-512	account_id	neuron_id
Motoko	173_412 ($\textcolor{red}{0.11\%}$)	297_725_367 ($\textcolor{red}{20.30\%}$)	281_729_738 ($\textcolor{red}{23.55\%}$)	37_735 ($\textcolor{red}{25.71\%}$)	27_166 ($\textcolor{red}{30.86\%}$)
Rust	478_873 ($\textcolor{green}{-0.02\%}$)	82_788_111 ($\textcolor{red}{0.33\%}$)	56_793_155 ($\textcolor{red}{0.47\%}$)	49_455 ($\textcolor{red}{16.59\%}$)	52_124 ($\textcolor{red}{17.35\%}$)

Certified map

	binary_size	generate 10k	max mem	inc	witness	upgrade
Motoko	206_652 ($\textcolor{red}{0.08\%}$)	5_254_991_528 ($\textcolor{red}{19.70\%}$)	3_430_044	623_666 ($\textcolor{red}{20.00\%}$)	436_318 ($\textcolor{red}{33.12\%}$)	274_614_372 ($\textcolor{red}{21.97\%}$)
Rust	503_545 ($\textcolor{green}{-0.02\%}$)	6_309_529_790 ($\textcolor{red}{1.78\%}$)	2_228_224	1_004_189 ($\textcolor{red}{2.10\%}$)	301_445 ($\textcolor{red}{4.56\%}$)	5_926_705_911 ($\textcolor{red}{1.89\%}$)

Statistics

binary_size: 0.04% [-0.05%, 0.12%]
max_mem: no change
cycles: 15.02% [10.02%, 20.01%]

Basic DAO

	binary_size	init	transfer_token	submit_proposal	vote_proposal	upgrade
Motoko	237_314 ($\textcolor{red}{0.19\%}$)	511_299 ($\textcolor{red}{2.76\%}$)	22_949 ($\textcolor{red}{41.21\%}$)	19_127 ($\textcolor{red}{50.89\%}$)	20_312 ($\textcolor{red}{43.89\%}$)	157_833 ($\textcolor{red}{22.53\%}$)
Rust	782_495 ($\textcolor{green}{-0.03\%}$)	613_885 ($\textcolor{red}{12.03\%}$)	101_922 ($\textcolor{red}{17.68\%}$)	126_043 ($\textcolor{red}{18.91\%}$)	137_819 ($\textcolor{red}{16.89\%}$)	1_825_018 ($\textcolor{red}{12.35\%}$)

DIP721 NFT

	binary_size	init	mint_token	transfer_token	upgrade
Motoko	195_621 ($\textcolor{red}{0.25\%}$)	481_132 ($\textcolor{red}{1.88\%}$)	29_869 ($\textcolor{red}{33.60\%}$)	8_896 ($\textcolor{red}{88.12\%}$)	89_994 ($\textcolor{red}{25.69\%}$)
Rust	804_148 ($\textcolor{green}{-0.03\%}$)	240_775 ($\textcolor{red}{10.84\%}$)	369_710 ($\textcolor{red}{13.55\%}$)	91_916 ($\textcolor{red}{17.62\%}$)	2_014_186 ($\textcolor{red}{12.08\%}$)

Statistics

binary_size: 0.10% [-0.08%, 0.27%]
max_mem: no change
cycles: 24.58% [16.02%, 33.15%]

Heartbeat

	binary_size	heartbeat
Motoko	123_885 ($\textcolor{red}{0.15\%}$)	23_310 ($\textcolor{red}{215.04\%}$)
Rust	23_843 ($\textcolor{red}{0.02\%}$)	546 ($\textcolor{green}{-30.45\%}$)

Timer

	binary_size	setTimer	cancelTimer
Motoko	130_153 ($\textcolor{red}{0.14\%}$)	52_177 ($\textcolor{red}{242.66\%}$)	4_653 ($\textcolor{red}{176.31\%}$)
Rust	423_499 ($\textcolor{green}{-0.03\%}$)	68_210 ($\textcolor{red}{56.91\%}$)	11_167 ($\textcolor{red}{47.54\%}$)

Statistics

binary_size: 0.06% [-0.50%, 0.61%]
max_mem: no change
cycles: 130.85% [19.27%, 242.43%]

Garbage Collection

	generate 700k	max mem	batch_get 50	batch_put 50	batch_remove 50
default	1_171_382_327 ($\textcolor{red}{32.20\%}$)	51_991_392	119 ($\textcolor{red}{138.00\%}$)	119 ($\textcolor{red}{138.00\%}$)	119 ($\textcolor{red}{138.00\%}$)
copying	1_171_382_209 ($\textcolor{red}{32.20\%}$)	51_991_392	1_171_104_158 ($\textcolor{red}{32.18\%}$)	1_171_195_718 ($\textcolor{red}{32.18\%}$)	1_171_106_971 ($\textcolor{red}{32.18\%}$)
compacting	1_672_114_728 ($\textcolor{red}{14.12\%}$)	51_991_392	1_290_052_240 ($\textcolor{red}{13.99\%}$)	1_533_417_914 ($\textcolor{red}{14.62\%}$)	1_564_512_328 ($\textcolor{red}{14.69\%}$)
generational	2_529_073_463 ($\textcolor{red}{15.76\%}$)	51_999_856	999_515_223 ($\textcolor{red}{16.81\%}$)	1_232_308 ($\textcolor{red}{16.50\%}$)	1_103_421 ($\textcolor{red}{16.40\%}$)
incremental	29_503_121 ($\textcolor{red}{3.45\%}$)	985_885_652	333_756_008 ($\textcolor{red}{14.98\%}$)	336_886_802 ($\textcolor{red}{14.98\%}$)	336_875_628 ($\textcolor{red}{14.98\%}$)

Actor class

	binary size	put new bucket	put existing bucket	get
Map	261_945 ($\textcolor{red}{0.11\%}$)	715_767 ($\textcolor{red}{9.36\%}$)	16_296 ($\textcolor{red}{265.46\%}$)	16_803 ($\textcolor{red}{241.59\%}$)

Statistics

binary_size: no change
max_mem: no change
cycles: 52.61% [26.58%, 78.65%]

Publisher & Subscriber

	pub_binary_size	sub_binary_size	subscribe_caller	subscribe_callee	publish_caller	publish_callee
Motoko	145_023 ($\textcolor{red}{0.18\%}$)	131_856 ($\textcolor{red}{0.17\%}$)	28_786 ($\textcolor{red}{96.48\%}$)	11_976 ($\textcolor{red}{41.63\%}$)	23_098 ($\textcolor{red}{119.17\%}$)	6_439 ($\textcolor{red}{75.50\%}$)
Rust	458_294 ($\textcolor{green}{-0.03\%}$)	511_783 ($\textcolor{green}{-0.02\%}$)	69_854 ($\textcolor{red}{35.30\%}$)	42_859 ($\textcolor{red}{24.53\%}$)	92_892 ($\textcolor{red}{24.86\%}$)	52_112 ($\textcolor{red}{18.41\%}$)

Statistics

binary_size: 0.07% [-0.06%, 0.21%]
max_mem: no change
cycles: 54.49% [29.17%, 79.80%]

Overall Statistics
binary_size: 0.05% [0.02%, 0.07%]
max_mem: no change
cycles: 30.88% [26.00%, 35.76%]

Note The flamegraph link only works after you merge. Unchanged benchmarks are omitted.

Collection libraries

Measure different collection libraries written in both Motoko and Rust. The library names with _rs suffix are written in Rust; the rest are written in Motoko. The _stable and _stable_rs suffix represents that the library directly writes the state to stable memory using Region in Motoko and ic-stable-stuctures in Rust.

We use the same random number generator with fixed seed to ensure that all collections contain the same elements, and the queries are exactly the same. Below we explain the measurements of each column in the table:

generate 1m. Insert 1m Nat64 integers into the collection. For Motoko collections, it usually triggers the GC; the rest of the column are not likely to trigger GC.
max mem. For Motoko, it reports rts_max_heap_size after generate call; For Rust, it reports the Wasm's memory page * 32Kb.
batch_get 50. Find 50 elements from the collection.
batch_put 50. Insert 50 elements to the collection.
batch_remove 50. Remove 50 elements from the collection.
upgrade. Upgrade the canister with the same Wasm module. For non-stable benchmarks, the map state is persisted by serializing and deserializing states into stable memory. For stable benchmarks, the upgrade takes no cycles, as the state is already in the stable memory.

💎 Takeaways

The platform only charges for instruction count. Data structures which make use of caching and locality have no impact on the cost.
We have a limit on the maximal cycles per round. This means asymptotic behavior doesn't matter much. We care more about the performance up to a fixed N. In the extreme cases, you may see an $O(10000 n\log n)$ algorithm hitting the limit, while an $O(n^2)$ algorithm runs just fine.
Amortized algorithms/GC may need to be more eager to avoid hitting the cycle limit on a particular round.
Rust costs more cycles to process complicated Candid data, but it is more efficient in performing core computations.

Note

The Candid interface of the benchmark is minimal, therefore the serialization cost is negligible in this measurement.

Due to the instrumentation overhead and cycle limit, we cannot profile computations with very large collections.

The upgrade column uses Candid for serializing stable data. In Rust, you may get better cycle cost by using a different serialization format. Another slowdown in Rust is that ic-stable-structures tends to be slower than the region memory in Motoko.

Different library has different ways for persisting data during upgrades, there are mainly three categories:

Use stable variable directly in Motoko: zhenya_hashmap, btree, vector

Expose and serialize external state (share/unshare in Motoko, candid::Encode in Rust): rbtree, heap, btreemap_rs, hashmap_rs, heap_rs, vector_rs

Use pre/post-upgrade hooks to convert data into an array: hashmap, splay, triemap, buffer, imrc_hashmap_rs

The stable benchmarks are much more expensive than their non-stable counterpart, because the stable memory API is much more expensive. The benefit is that they get fast upgrade. The upgrade still needs to parse the metadata when initializing the upgraded Wasm module.

hashmap uses amortized data structure. When the initial capacity is reached, it has to copy the whole array, thus the cost of batch_put 50 is much higher than other data structures.

btree comes from mops.one/stableheapbtreemap.

zhenya_hashmap comes from mops.one/map.

vector comes from mops.one/vector. Compare with buffer, put has better worst case time and space complexity ($O(\sqrt{n})$ vs $O(n)$); get has a slightly larger constant overhead.

hashmap_rs uses the fxhash crate, which is the same as std::collections::HashMap, but with a deterministic hasher. This ensures reproducible result.

imrc_hashmap_rs uses the im-rc crate, which is the immutable version hashmap in Rust.

Map

	binary_size	generate 1m	max mem	batch_get 50	batch_put 50	batch_remove 50	upgrade
hashmap	160_407	8_550_261_900	61_987_852	349_808	6_641_222_848	377_790	11_273_695_870
triemap	163_606	15_268_684_428	74_216_172	301_412	737_508	722_627	17_302_961_961
rbtree	158_225	7_665_886_603	57_996_060	115_637	346_274	370_932	7_231_296_002
splay	160_055	15_388_999_493	53_995_996	738_550	777_813	1_077_553	4_832_227_514
btree	188_004	11_040_703_048	31_104_012	376_209	519_468	577_253	3_162_844_776
zhenya_hashmap	160_784	2_838_455_412	22_773_100	66_353	84_294	96_614	3_353_572_476
btreemap_rs	478_653	1_797_168_137	27_590_656	75_573	125_437	86_323	2_941_065_080
imrc_hashmap_rs	482_783	2_584_652_919	244_973_568	38_439	179_288	115_588	5_796_576_276
hashmap_rs	469_075	433_765_793	73_138_176	21_856	26_958	25_223	1_293_479_144

Priority queue

	binary_size	heapify 1m	max mem	pop_min 50	put 50	pop_min 50	upgrade
heap	147_908	6_393_606_585	29_995_956	701_835	258_841	668_731	3_337_783_210
heap_rs	462_827	138_669_875	18_284_544	57_564	23_346	57_696	511_961_256

Growable array

	binary_size	generate 5k	max mem	batch_get 500	batch_put 500	batch_remove 500	upgrade
buffer	151_225	2_811_683	65_644	109_527	884_994	178_027	3_206_695
vector	152_845	2_228_708	24_580	146_173	212_398	203_951	4_810_168
vec_rs	460_616	289_093	1_310_720	17_300	30_623	25_759	3_171_850

Stable structures

	binary_size	generate 50k	max mem	batch_get 50	batch_put 50	batch_remove 50	upgrade
btreemap_rs	478_653	76_392_041	2_555_904	65_131	97_327	85_332	126_467_483
btreemap_stable_rs	488_655	5_255_681_694	2_031_616	3_167_281	5_784_578	9_888_420	731_129
heap_rs	462_827	7_001_771	2_293_760	50_073	23_594	50_045	26_819_762
heap_stable_rs	450_750	319_633_530	458_752	2_674_744	278_372	2_654_546	731_276
vec_rs	460_616	3_079_437	2_228_224	17_300	18_473	18_000	24_772_373
vec_stable_rs	448_692	75_145_339	458_752	70_326	91_522	93_718	731_289

Environment

dfx 0.15.2-beta.1

Motoko compiler 0.10.0 (source a3ywvw0a-p5a03qy6-vscbl9j8-qxszbxa6)

rustc 1.73.0 (cc66ad468 2023-10-03)

ic-repl 0.6.0

ic-wasm 0.7.0
Cryptographic libraries

Measure different cryptographic libraries written in both Motoko and Rust.

SHA-2 benchmarks
- SHA-256/SHA-512. Compute the hash of a 1M Wasm binary.
- account_id. Compute the ledger account id from principal, based on SHA-224.
- neuron_id. Compute the NNS neuron id from principal, based on SHA-256.
Certified map. Merkle Tree for storing key-value pairs and generate witness according to the IC Interface Specification.
- generate 10k. Insert 10k 7-character word as both key and value into the certified map.
- max mem. For Motoko, it reports rts_max_heap_size after generate call; For Rust, it reports the Wasm's memory page * 32Kb.
- inc. Increment a counter and insert the counter value into the map.
- witness. Generate the root hash and a witness for the counter.
- upgrade. Upgrade the canister with the same Wasm. In Motoko, we use stable variable. In Rust, we convert the tree to a vector before serialization.

SHA-2

	binary_size	SHA-256	SHA-512	account_id	neuron_id
Motoko	173_412	297_725_367	281_729_738	37_735	27_166
Rust	478_873	82_788_111	56_793_155	49_455	52_124

Certified map

	binary_size	generate 10k	max mem	inc	witness	upgrade
Motoko	206_652	5_254_991_528	3_430_044	623_666	436_318	274_614_372
Rust	503_545	6_309_529_790	2_228_224	1_004_189	301_445	5_926_705_911

Environment

dfx 0.15.2-beta.1

Motoko compiler 0.10.0 (source a3ywvw0a-p5a03qy6-vscbl9j8-qxszbxa6)

rustc 1.73.0 (cc66ad468 2023-10-03)

ic-repl 0.6.0

ic-wasm 0.7.0
Sample Dapps

Measure the performance of some typical dapps:

Basic DAO, with heartbeat disabled to make profiling easier. We have a separate benchmark to measure heartbeat performance.
DIP721 NFT

Note

The cost difference is mainly due to the Candid serialization cost.

Motoko statically compiles/specializes the serialization code for each method, whereas in Rust, we use serde to dynamically deserialize data based on data on the wire.

We could improve the performance on the Rust side by using parser combinators. But it is a challenge to maintain the ergonomics provided by serde.

For real-world applications, we tend to send small data for each endpoint, which makes the Candid overhead in Rust tolerable.

Basic DAO

	binary_size	init	transfer_token	submit_proposal	vote_proposal	upgrade
Motoko	237_314	511_299	22_949	19_127	20_312	157_833
Rust	782_495	613_885	101_922	126_043	137_819	1_825_018

DIP721 NFT

	binary_size	init	mint_token	transfer_token	upgrade
Motoko	195_621	481_132	29_869	8_896	89_994
Rust	804_148	240_775	369_710	91_916	2_014_186

Environment

dfx 0.15.2-beta.1

Motoko compiler 0.10.0 (source a3ywvw0a-p5a03qy6-vscbl9j8-qxszbxa6)

rustc 1.73.0 (cc66ad468 2023-10-03)

ic-repl 0.6.0

ic-wasm 0.7.0
Heartbeat / Timer

Measure the cost of empty heartbeat and timer job.

setTimer measures both the setTimer(0) method and the execution of empty job.
It is not easy to reliably capture the above events in one flamegraph, as the implementation detail of the replica can affect how we measure this. Typically, a correct flamegraph contains both setTimer and canister_global_timer function. If it's not there, we may need to adjust the script.

Heartbeat

	binary_size	heartbeat
Motoko	123_885	23_310
Rust	23_843	546

Timer

	binary_size	setTimer	cancelTimer
Motoko	130_153	52_177	4_653
Rust	423_499	68_210	11_167

Environment

dfx 0.15.2-beta.1

Motoko compiler 0.10.0 (source a3ywvw0a-p5a03qy6-vscbl9j8-qxszbxa6)

rustc 1.73.0 (cc66ad468 2023-10-03)

ic-repl 0.6.0

ic-wasm 0.7.0
Motoko Specific Benchmarks

Measure various features only available in Motoko.

Garbage Collection. Measure Motoko garbage collection cost using the Triemap benchmark. The max mem column reports rts_max_heap_size after generate call. The cycle cost numbers reported here are garbage collection cost only. Some flamegraphs are truncated due to the 2M log size limit. The dfx/ic-wasm optimizer is disabled for the garbage collection test cases due to how the optimizer affects function names, making profiling trickier.
- default. Compile with the default GC option. With the current GC scheduler, generate will trigger the copying GC. The rest of the methods will not trigger GC.
- copying. Compile with --force-gc --copying-gc.
- compacting. Compile with --force-gc --compacting-gc.
- generational. Compile with --force-gc --generational-gc.
- incremental. Compile with --force-gc --incremental-gc.
Actor class. Measure the cost of spawning actor class, using the Actor classes example.

Garbage Collection

	generate 700k	max mem	batch_get 50	batch_put 50	batch_remove 50
default	1_171_382_327	51_991_392	119	119	119
copying	1_171_382_209	51_991_392	1_171_104_158	1_171_195_718	1_171_106_971
compacting	1_672_114_728	51_991_392	1_290_052_240	1_533_417_914	1_564_512_328
generational	2_529_073_463	51_999_856	999_515_223	1_232_308	1_103_421
incremental	29_503_121	985_885_652	333_756_008	336_886_802	336_875_628

Actor class

	binary size	put new bucket	put existing bucket	get
Map	261_945	715_767	16_296	16_803

Environment

dfx 0.15.2-beta.1

Motoko compiler 0.10.0 (source a3ywvw0a-p5a03qy6-vscbl9j8-qxszbxa6)

rustc 1.73.0 (cc66ad468 2023-10-03)

ic-repl 0.6.0

ic-wasm 0.7.0
Publisher & Subscriber

Measure the cost of inter-canister calls from the Publisher & Subscriber example.

	pub_binary_size	sub_binary_size	subscribe_caller	subscribe_callee	publish_caller	publish_callee
Motoko	145_023	131_856	28_786	11_976	23_098	6_439
Rust	458_294	511_783	69_854	42_859	92_892	52_112

Environment

dfx 0.15.2-beta.1

Motoko compiler 0.10.0 (source a3ywvw0a-p5a03qy6-vscbl9j8-qxszbxa6)

rustc 1.73.0 (cc66ad468 2023-10-03)

ic-repl 0.6.0

ic-wasm 0.7.0

dfinity / canister-profiling

bump ic-repl #102

Map

Priority queue

Growable array

Stable structures

Statistics

SHA-2

Certified map

Statistics

Basic DAO

DIP721 NFT

Statistics

Heartbeat

Timer

Statistics

Garbage Collection

Actor class

Statistics

Publisher & Subscriber

Statistics

Overall Statistics

Collection libraries

💎 Takeaways

Map

Priority queue

Growable array

Stable structures

Environment

Cryptographic libraries

SHA-2

Certified map

Environment

Sample Dapps

Basic DAO

DIP721 NFT

Environment

Heartbeat / Timer

Heartbeat

Timer

Environment

Motoko Specific Benchmarks

Garbage Collection

Actor class

Environment

Publisher & Subscriber

Environment