New format_args!() and fmt::Arguments implementation

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged

[m-ou-se]

Part of #99012

This is a new implementation of format_args!() and fmt::Arguments. With this implementation, fmt::Arguments is only two pointers in size. (Instead of six, before.) This makes it the same size as a &str and makes it fit in a register pair.

---

This fmt::Arguments can store a &'static strwithout any indirection or additional storage. This means that simple cases like print_fmt(format_args!("hello")) are now just as efficient for the caller as print_str("hello"), as shown by this example:

code:

fnmain(){println!("Hello, world!");}

before:

main:subrsp,56learax,[rip+ .Lanon_hello_world]mov qword ptr [rsp+8],raxmov qword ptr [rsp+16],1mov qword ptr [rsp+24],8xorpsxmm0,xmm0movups xmmword ptr [rsp+32],xmm0leardi,[rsp+8]call qword ptr [rip+std::io::stdio::_print]addrsp,56ret

after:

main:learsi,[rip+ .Lanon_hello_world]movedi,29jmp qword ptr [rip+std::io::stdio::_print]

(panic!("Hello, world!"); shows a similar change.)

---

This implementation stores all static information as just a single (byte) string, without any indirection:

code:

format_args!("Hello, {name:-^20}!")

lowering before:

fmt::Arguments::new_v1_formatted(&["Hello, ","!\n"],&args,&[Placeholder{position:0usize,flags:3355443245u32,precision: format_count::Implied,width: format_count::Is(20u16),},],)

lowering after:

fmt::Arguments::new(b"\x07Hello, \xc3-\x00\x00\xc8\x14\x00\x02!\n\x00",&args,)

This saves a ton of pointers and simplifies the expansion significantly, but does mean that individual pieces (e.g. "Hello, " and "!\n") cannot be reused. (Those pieces are often smaller than a pointer to them, though, in which case reusing them is useless.)

---

The details of the new representation are documented in library/core/src/fmt/mod.rs.

---

Diagram of the data structure after this change:

Original data structure

[m-ou-se]

@bors try @rust-timer queue

[rust-bors]

☀️ Try build successful (CI)
Build commit: 6e6ba94 (6e6ba949d24fbfbd9cd48ca4c98adf59fbd04482, parent: a7b3715826827677ca8769eb88dc8052f43e734b)

[rust-timer]

Finished benchmarking commit (6e6ba94): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking this pull request means it may be perf-sensitive – we'll automatically label it not fit for rolling up. You can override this, but we strongly advise not to, due to possible changes in compiler perf.

Next Steps: If you can justify the regressions found in this try perf run, please do so in sufficient writing along with @rustbot label: +perf-regression-triaged. If not, please fix the regressions and do another perf run. If its results are neutral or positive, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.8%]	26
Regressions ❌ (secondary)	0.6%	[0.1%, 1.3%]	44
Improvements ✅ (primary)	-0.7%	[-4.3%, -0.1%]	109
Improvements ✅ (secondary)	-1.7%	[-38.2%, -0.0%]	93
All ❌✅ (primary)	-0.5%	[-4.3%, 5.8%]	135

Max RSS (memory usage)

Results (primary -1.5%, secondary -0.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	2.2%	[2.2%, 2.2%]	1
Regressions ❌ (secondary)	3.7%	[1.0%, 6.7%]	12
Improvements ✅ (primary)	-1.6%	[-6.0%, -0.5%]	31
Improvements ✅ (secondary)	-2.6%	[-7.9%, -0.7%]	25
All ❌✅ (primary)	-1.5%	[-6.0%, 2.2%]	32

Cycles

Results (primary -0.5%, secondary -4.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	4.8%	[3.4%, 6.2%]	2
Regressions ❌ (secondary)	8.8%	[2.6%, 18.8%]	6
Improvements ✅ (primary)	-3.1%	[-5.0%, -2.1%]	4
Improvements ✅ (secondary)	-10.3%	[-39.4%, -2.1%]	13
All ❌✅ (primary)	-0.5%	[-5.0%, 6.2%]	6

Binary size

Results (primary -0.7%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.2%	[0.0%, 7.5%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.7%	[-3.3%, 1.4%]	133

Bootstrap: 476.631s -> 471.922s (-0.99%)
Artifact size: 391.32 MiB -> 388.56 MiB (-0.70%)

[m-ou-se]

Ooh that's pretty good :D

[m-ou-se]

Pretty much everything looks like a great improvement. Not only number of instructions executed, but also memory usage and binary size. 🎉

Only two significant negative results:

1. "image-0.25.6 opt incr-patched:println" with almost +6% instructions:u.

Looking at the detailed results, it looks like that's all LLVM. Probably because llvm got more optimization opportunities. That's not necessarily a bad thing.

2. The fmt-write-str runtime benchmark with over +12% instructions:u.

This could be concerning, but I can't seem to fully replicate it locally.

If I recompile and run this benchmark 100 times in both nightly and with this PR, I do get this interesting result though:

With the nightly compiler, the results vary, with many measurements clustered close to 25ms but also many around 40ms. With this PR, the results are very consistent, all clustered around 27ms. (Update: It's around 26ms now, after a minor optimization.)

So, the median result is worse, but the average is better.

My guess is that the indirection (a slice of string slices) can make things unpredictable, as the strings aren't always in the optimal place for caching. The lack of indirection in the new version then makes it much more predictable. This is just a guess though.

[m-ou-se]

@bors try @rust-timer queue

[rust-timer]

Finished benchmarking commit (503dce3): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Our benchmarks found a performance regression caused by this PR.
This might be an actual regression, but it can also be just noise.

Next Steps:

• If the regression was expected or you think it can be justified,
  please write a comment with sufficient written justification, and add
  @rustbot label: +perf-regression-triaged to it, to mark the regression as triaged.
• If you think that you know of a way to resolve the regression, try to create
  a new PR with a fix for the regression.
• If you do not understand the regression or you think that it is just noise,
  you can ask the @rust-lang/wg-compiler-performance working group for help (members of this group
  were already notified of this PR).

@rustbot label: +perf-regression
cc @rust-lang/wg-compiler-performance

Instruction count

Our most reliable metric. Used to determine the overall result above. However, even this metric can be noisy.

	mean	range	count
Regressions ❌ (primary)	0.7%	[0.1%, 5.7%]	17
Regressions ❌ (secondary)	0.6%	[0.1%, 1.1%]	40
Improvements ✅ (primary)	-0.7%	[-4.4%, -0.1%]	120
Improvements ✅ (secondary)	-1.6%	[-38.5%, -0.0%]	106
All ❌✅ (primary)	-0.5%	[-4.4%, 5.7%]	137

Max RSS (memory usage)

Results (primary -1.5%, secondary -1.6%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	3.8%	[1.4%, 7.0%]	3
Regressions ❌ (secondary)	3.8%	[1.2%, 5.8%]	8
Improvements ✅ (primary)	-2.2%	[-6.0%, -0.6%]	23
Improvements ✅ (secondary)	-3.1%	[-7.3%, -0.6%]	29
All ❌✅ (primary)	-1.5%	[-6.0%, 7.0%]	26

Cycles

Results (primary -2.3%, secondary 0.4%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	5.2%	[3.4%, 6.9%]	2
Regressions ❌ (secondary)	7.6%	[1.6%, 18.5%]	19
Improvements ✅ (primary)	-4.4%	[-7.9%, -1.5%]	7
Improvements ✅ (secondary)	-11.0%	[-40.0%, -1.8%]	12
All ❌✅ (primary)	-2.3%	[-7.9%, 6.9%]	9

Binary size

Results (primary -0.8%, secondary -1.3%)

A less reliable metric. May be of interest, but not used to determine the overall result above.

	mean	range	count
Regressions ❌ (primary)	0.5%	[0.0%, 1.4%]	4
Regressions ❌ (secondary)	3.0%	[0.0%, 6.9%]	12
Improvements ✅ (primary)	-0.8%	[-3.3%, -0.0%]	129
Improvements ✅ (secondary)	-1.7%	[-23.6%, -0.0%]	123
All ❌✅ (primary)	-0.8%	[-3.3%, 1.4%]	133

Bootstrap: 476.356s -> 473.309s (-0.64%)
Artifact size: 391.04 MiB -> 388.34 MiB (-0.69%)

[panstromek]

Perf triage:

Improvements outweigh regressions.

@rustbot label: +perf-regression-triaged