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31 files changed, 272 insertions, 2 deletions
diff --git a/CHECKPOINT.md b/CHECKPOINT.md index f9c180a..c0d099c 100644 --- a/CHECKPOINT.md +++ b/CHECKPOINT.md @@ -13,7 +13,7 @@ | 영역 | 확인한 것 | 근거 | |---|---|---| | 앱 표현 | 상태(수, `bool`, 정확한 64비트 정수 `i64`, text와 커서·마크, 레코드의 리스트와 키 있는 리스트, 인덱스), 입력(키, text, 필드 있는 메시지, 타이머), 원자적 이벤트 핸들러, 순수 보기(조건식, 표와 걸러진 표, count·sum·max·min·first), `fn`·`use` 라이브러리, text 비교, 시간(`now`, `every`, `floor`, `%`). 로드할 때 타입·스택·합류·커서와 인덱스의 소속을 모두 검증하고 이벤트의 실행량에 상한이 있다 | 008, [016](docs/design/016-bool-and-i64.md), aup `docs/design/002-dsl-direction.md`, aup `make check`(파이썬 참조 모델 대조, 진단 223건) | -| 수명과 계산 | 값의 수명은 선언이 말한다: `state`(저장), `transient state`(앱이 도는 동안: 저장소에 쓰지 않고 다시 시작하면 초기값, SD 카드에서 쓰기 17배), `let`(이벤트 동안). 핸들러와 보기가 계산한다: 이벤트의 리스트(`let seen: list of Seen by node`), 세는 `for i in a .. b`, `break`, 8겹까지의 중첩, 그리고 `view 이름(인자) { … return … }`(스냅숏에서 돌아 소유자를 막지 않는다). 모든 반복은 시작할 때 횟수의 상한을 갖고, 모든 이벤트와 보기는 실행량 예산(정하지 않으면 2^28 명령)과 메모리 몫(2^28 바이트) 안에서 끝난다. 노드 10만·간선 100만의 BFS 한 이벤트가 HTTP로 90 ms였고(처음 397, 020 뒤 191; CPython 452, C 9.1, 123), 022 뒤 코어는 7.4 ms다(같은 프로세스의 C 9.9): 많이 찾는 저장된 리스트를 배열과 칸의 색인으로 펴고, 열을 값만큼 좁히고, 루프 묶음을 레지스터의 기계어로 돈다(리눅스 AArch64의 JIT; 다른 곳은 실행기, 답은 같다). 다만 C를 넘은 것은 미리 읽기 덕이고, 끄면 15.7 ms로 C의 1.57배다. 일곱 가지 일(실수 루프, 배낭, 정렬, 조인, 텍스트, 행렬, BFS)로 C와 견주면 124에서는 3–300배 느렸고, 023의 계층과 표현(HASHED: 차례를 어긴 키는 해시 표의 칸에, 위치가 필요할 때 정렬)으로 지금은 1.19–5.58배(기하 평균 1.92)다(125). Pure의 표현과 뜻대로 손으로 쓴 바닥은 C의 0.90배이고 뜻의 검사는 끌어내면 0–3%라, 막는 것은 실행 계층이다(124). 모든 블록을 SSA로 올리는 최적화 계층(023)의 첫 걸음들이 들어갔고, 텍스트(실행기로 돈다)와 BFS(계층이 덧붙이기를 못 한다)가 남았다. 기계어를 만들지 않는 길로, 루프를 회차 256개의 묶음으로 돌고 연산마다 빌드 때 만든 C 루프를 쓰는 묶음 실행기(024)를 시제품으로 재니 연산을 따로 해석하면 roots 0.99배, 배낭 0.71배(4바이트 레인), BFS 1.03배, join 1.77배, 행렬 곱 2.50배이고, 행렬 곱은 곱해 더하기를 합치면 0.94배였다(계층 1.20–2.46배, 기하 평균 1.92 대 1.58, 합친 꼴로 1.24; 041, 손으로 짠 천장). 1단계(세는 루프의 레인 꼴 몸체, 회차 1024개씩)가 들어가 knapsack이 실행기에서 1,041 ms에서 13.6 ms가 됐다(계층 7.5, 안쪽 루프는 1.17배). 묶음 루프가 없는 모듈의 실행기는 명령과 사이클이 그대로다(126). 2단계(중첩 루프를 레인마다 함께, `x = x + e`·`min`·`max` 모으기)로 roots가 9.13 ms가 되어 기계어 없이 계층(9.57)보다 빠르고, matmul은 914.9에서 50.0 ms다(계층 14.3, 127). 덧붙이기, 점화식, 칸에 더하기, 걷기를 묶어 join이 실행기의 423에서 161 ms가 됐다(계층 74). 남은 값은 덧붙이기 하나 약 100 ns(실행기와 같다), join의 점화식 회차당 약 60 ns, 레인이 적은 중첩 몸체의 해석이고, BFS는 묶이지 않아 기계어를 아직 걷어낼 수 없다(128). 덧붙이기를 리스트의 한 호출로, 점화식을 레지스터 꼴로, 모으기의 끝을 차례 없이 하자 knapsack 10.8, matmul 36.4, join 118, sort 55.5 ms가 됐다(기계어 7.9, 14.2, 72–79, 35.6; 129). BFS는 프런티어 묶음으로 셈하면 차례대로 할 꼬리가 간선의 약 10%다(129). 가드 루프, 묶음 안의 걷기, 커지기만 하는 걸러내기로 BFS도 묶음으로 돌아 93에서 41 ms가 됐다(기계어 7.7, C 10). 간선당 명령 211개 대 38.5개이고, 이 꼴의 바닥(약 50개)이 기계어 위라서 기계어를 걷어내려면 합친 연산이 필요하다(130). 범용 장치만으로(같은 코드의 값 다시 쓰기, 고르기, 비트로 묻기, 아핀 `first + i`) 간선당 112개, 24.0 ms가 됐고, 범용의 바닥은 기계어의 약 2배로 보인다(131). 레지스터 타일 해석기를 시제품으로 재니(133) 산수의 사슬은 C보다 빠르고(roots 5.8 ms) 모으기가 있는 몸체는 졌으며(배낭 4배, BFS 2.4배), 같은 자리에서 꽉 짠 훑기가 BFS 기계어의 1.2배·배낭 0.4배였다: 훑기의 꼴은 옳고 3배는 구현이라, 묶음 프로그램을 로드 때 한 번 만들고 루프를 꽉 짜는 길로 간다. 그 값을 재니 배낭에서 묶음마다 0.90 µs(시간의 38%)이고, 블록의 모양에서 나오는 사실은 로드 때, 값에서 나오는 사실만 묶음마다 보는 설계를 다섯 단계로 세웠다(025). 1단계(블록의 사실을 로드 때 한 번)로 배낭의 묶음마다 값이 0.90에서 0.68 µs, 배낭이 11.48에서 10.34 ms가 됐다. 막대(0.60 µs, 10.3 ms)에는 못 미쳤고, 남은 값은 명령마다의 해석이다(134). 2단계(균일·아핀 조각을 스칼라로 한 번에)는 matmul을 38.2에서 36.1 ms로 줄였지만(중첩 회차의 해석) 배낭의 묶음마다 값은 0.63 µs에 머물렀다: 그 값은 키로 찾기와 레인 연산의 준비에 있다(135). 다음은 요소마다다. TPC-C −2.8%(기준 3% 안), 은행 질의의 명령 수는 1% 안. 같은 계산이 Pi(JIT)·WSL2·M3 Mac에서 같다. 같은 탐색을 보기로 하면 쓰기는 CPU를 나누는 만큼만 줄고(이벤트로 하면 0.2%로 멈춘다), 본문이 있는 보기는 보기의 스레드(`--view-workers`)가 계산해 연결 스레드를 막지 않는다(쓰기 최대 지연이 CPU만 나눌 때의 1.0배, 연결 스레드 하나에서 묻는 연결 둘이 1.95배) | [018](docs/design/018-lifetimes-and-computation.md), [020](docs/design/020-computing-faster.md), [117](docs/research/117-transient-states.md), [118](docs/research/118-computing-in-one-event.md), [119](docs/research/119-views-that-compute.md), [121](docs/research/121-computing-faster.md), [122](docs/research/122-views-off-the-connection-threads.md), [021](docs/design/021-past-c.md), [123](docs/research/123-past-c.md), [022](docs/design/022-arrays-and-registers.md), [124](docs/research/124-against-c.md), [023](docs/design/023-optimizing-tier.md), [125](docs/research/125-tier-first-steps.md), [024](docs/design/024-batch-executor.md), [126](docs/research/126-batch-executor-stage-one.md), [127](docs/research/127-batch-executor-stage-two.md), [128](docs/research/128-batch-executor-tables-and-costs.md), [129](docs/research/129-batch-executor-costs-cut.md), [130](docs/research/130-batch-executor-frontiers.md), [131](docs/research/131-batch-executor-general-cuts.md), [132](docs/research/132-batch-executor-floor-and-the-way-past.md), [133](docs/research/133-register-tiles-measured.md), [025](docs/design/025-batch-programs.md), [134](docs/research/134-batch-plans-stage-one.md), [135](docs/research/135-batch-plans-stage-two.md) | +| 수명과 계산 | 값의 수명은 선언이 말한다: `state`(저장), `transient state`(앱이 도는 동안: 저장소에 쓰지 않고 다시 시작하면 초기값, SD 카드에서 쓰기 17배), `let`(이벤트 동안). 핸들러와 보기가 계산한다: 이벤트의 리스트(`let seen: list of Seen by node`), 세는 `for i in a .. b`, `break`, 8겹까지의 중첩, 그리고 `view 이름(인자) { … return … }`(스냅숏에서 돌아 소유자를 막지 않는다). 모든 반복은 시작할 때 횟수의 상한을 갖고, 모든 이벤트와 보기는 실행량 예산(정하지 않으면 2^28 명령)과 메모리 몫(2^28 바이트) 안에서 끝난다. 노드 10만·간선 100만의 BFS 한 이벤트가 HTTP로 90 ms였고(처음 397, 020 뒤 191; CPython 452, C 9.1, 123), 022 뒤 코어는 7.4 ms다(같은 프로세스의 C 9.9): 많이 찾는 저장된 리스트를 배열과 칸의 색인으로 펴고, 열을 값만큼 좁히고, 루프 묶음을 레지스터의 기계어로 돈다(리눅스 AArch64의 JIT; 다른 곳은 실행기, 답은 같다). 다만 C를 넘은 것은 미리 읽기 덕이고, 끄면 15.7 ms로 C의 1.57배다. 일곱 가지 일(실수 루프, 배낭, 정렬, 조인, 텍스트, 행렬, BFS)로 C와 견주면 124에서는 3–300배 느렸고, 023의 계층과 표현(HASHED: 차례를 어긴 키는 해시 표의 칸에, 위치가 필요할 때 정렬)으로 지금은 1.19–5.58배(기하 평균 1.92)다(125). Pure의 표현과 뜻대로 손으로 쓴 바닥은 C의 0.90배이고 뜻의 검사는 끌어내면 0–3%라, 막는 것은 실행 계층이다(124). 모든 블록을 SSA로 올리는 최적화 계층(023)의 첫 걸음들이 들어갔고, 텍스트(실행기로 돈다)와 BFS(계층이 덧붙이기를 못 한다)가 남았다. 기계어를 만들지 않는 길로, 루프를 회차 256개의 묶음으로 돌고 연산마다 빌드 때 만든 C 루프를 쓰는 묶음 실행기(024)를 시제품으로 재니 연산을 따로 해석하면 roots 0.99배, 배낭 0.71배(4바이트 레인), BFS 1.03배, join 1.77배, 행렬 곱 2.50배이고, 행렬 곱은 곱해 더하기를 합치면 0.94배였다(계층 1.20–2.46배, 기하 평균 1.92 대 1.58, 합친 꼴로 1.24; 041, 손으로 짠 천장). 1단계(세는 루프의 레인 꼴 몸체, 회차 1024개씩)가 들어가 knapsack이 실행기에서 1,041 ms에서 13.6 ms가 됐다(계층 7.5, 안쪽 루프는 1.17배). 묶음 루프가 없는 모듈의 실행기는 명령과 사이클이 그대로다(126). 2단계(중첩 루프를 레인마다 함께, `x = x + e`·`min`·`max` 모으기)로 roots가 9.13 ms가 되어 기계어 없이 계층(9.57)보다 빠르고, matmul은 914.9에서 50.0 ms다(계층 14.3, 127). 덧붙이기, 점화식, 칸에 더하기, 걷기를 묶어 join이 실행기의 423에서 161 ms가 됐다(계층 74). 남은 값은 덧붙이기 하나 약 100 ns(실행기와 같다), join의 점화식 회차당 약 60 ns, 레인이 적은 중첩 몸체의 해석이고, BFS는 묶이지 않아 기계어를 아직 걷어낼 수 없다(128). 덧붙이기를 리스트의 한 호출로, 점화식을 레지스터 꼴로, 모으기의 끝을 차례 없이 하자 knapsack 10.8, matmul 36.4, join 118, sort 55.5 ms가 됐다(기계어 7.9, 14.2, 72–79, 35.6; 129). BFS는 프런티어 묶음으로 셈하면 차례대로 할 꼬리가 간선의 약 10%다(129). 가드 루프, 묶음 안의 걷기, 커지기만 하는 걸러내기로 BFS도 묶음으로 돌아 93에서 41 ms가 됐다(기계어 7.7, C 10). 간선당 명령 211개 대 38.5개이고, 이 꼴의 바닥(약 50개)이 기계어 위라서 기계어를 걷어내려면 합친 연산이 필요하다(130). 범용 장치만으로(같은 코드의 값 다시 쓰기, 고르기, 비트로 묻기, 아핀 `first + i`) 간선당 112개, 24.0 ms가 됐고, 범용의 바닥은 기계어의 약 2배로 보인다(131). 레지스터 타일 해석기를 시제품으로 재니(133) 산수의 사슬은 C보다 빠르고(roots 5.8 ms) 모으기가 있는 몸체는 졌으며(배낭 4배, BFS 2.4배), 같은 자리에서 꽉 짠 훑기가 BFS 기계어의 1.2배·배낭 0.4배였다: 훑기의 꼴은 옳고 3배는 구현이라, 묶음 프로그램을 로드 때 한 번 만들고 루프를 꽉 짜는 길로 간다. 그 값을 재니 배낭에서 묶음마다 0.90 µs(시간의 38%)이고, 블록의 모양에서 나오는 사실은 로드 때, 값에서 나오는 사실만 묶음마다 보는 설계를 다섯 단계로 세웠다(025). 1단계(블록의 사실을 로드 때 한 번)로 배낭의 묶음마다 값이 0.90에서 0.68 µs, 배낭이 11.48에서 10.34 ms가 됐다. 막대(0.60 µs, 10.3 ms)에는 못 미쳤고, 남은 값은 명령마다의 해석이다(134). 2단계(균일·아핀 조각을 스칼라로 한 번에)는 matmul을 38.2에서 36.1 ms로 줄였지만(중첩 회차의 해석) 배낭의 묶음마다 값은 0.63 µs에 머물렀다: 그 값은 키로 찾기와 레인 연산의 준비에 있다(135). 다음은 요소마다다. 3단계(4바이트 곱하기, 레인 없이 시작하는 모으기, 리스트의 칸을 묶음에 한 번)로 b9 대비 matmul 40.0 → 26.0 ms, knapsack 11.5 → 10.1, roots 9.0 → 8.3이 됐고(기계어 14.2, 7.9, 9.57), 실행기와 은행 질의의 명령 수, TPC-C는 그대로다(136). TPC-C −2.8%(기준 3% 안), 은행 질의의 명령 수는 1% 안. 같은 계산이 Pi(JIT)·WSL2·M3 Mac에서 같다. 같은 탐색을 보기로 하면 쓰기는 CPU를 나누는 만큼만 줄고(이벤트로 하면 0.2%로 멈춘다), 본문이 있는 보기는 보기의 스레드(`--view-workers`)가 계산해 연결 스레드를 막지 않는다(쓰기 최대 지연이 CPU만 나눌 때의 1.0배, 연결 스레드 하나에서 묻는 연결 둘이 1.95배) | [018](docs/design/018-lifetimes-and-computation.md), [020](docs/design/020-computing-faster.md), [117](docs/research/117-transient-states.md), [118](docs/research/118-computing-in-one-event.md), [119](docs/research/119-views-that-compute.md), [121](docs/research/121-computing-faster.md), [122](docs/research/122-views-off-the-connection-threads.md), [021](docs/design/021-past-c.md), [123](docs/research/123-past-c.md), [022](docs/design/022-arrays-and-registers.md), [124](docs/research/124-against-c.md), [023](docs/design/023-optimizing-tier.md), [125](docs/research/125-tier-first-steps.md), [024](docs/design/024-batch-executor.md), [126](docs/research/126-batch-executor-stage-one.md), [127](docs/research/127-batch-executor-stage-two.md), [128](docs/research/128-batch-executor-tables-and-costs.md), [129](docs/research/129-batch-executor-costs-cut.md), [130](docs/research/130-batch-executor-frontiers.md), [131](docs/research/131-batch-executor-general-cuts.md), [132](docs/research/132-batch-executor-floor-and-the-way-past.md), [133](docs/research/133-register-tiles-measured.md), [025](docs/design/025-batch-programs.md), [134](docs/research/134-batch-plans-stage-one.md), [135](docs/research/135-batch-plans-stage-two.md), [136](docs/research/136-batch-executor-stage-three.md) | | 보기 밀기 | 보기의 `GET`에 `Accept: text/event-stream`이면 그 값을 민다(SSE, 브라우저의 `EventSource` 그대로). 같은 보기와 인자를 보는 구독자는 계산 한 번을 나누고, 값이 바뀔 때만, 많아야 10 ms마다 한 번 보낸다. 느린 구독자에게는 가장 새 값 하나만 기다리게 한다. 모듈이 바뀌어도 같은 이름의 보기로 이어 가고, 토큰을 빼면 끊는다. 구독자 1,000에 쓰기 초당 100번까지 신선도 p99 11 ms 이하, 초당 1번이면 100 ms 폴링의 약 10분의 1 CPU(이벤트 하나와 요청 하나의 값이 같아 메시지 수의 비다), 구독자 1만에 구독자마다 0.3–0.4 KiB, 1만에게 퍼지기까지 p99 45 ms | [019](docs/design/019-pushing-views.md), [120](docs/research/120-pushing-views.md) | | 영속 | 선언한 상태가 곧 영속 상태다. 목록은 이미지와 로그(저장마다 바뀐 기록 한 항목, 재사용하는 할당 구간, 앞 항목의 다이제스트로 이어짐)에, 나머지는 트리 저장소에(커밋당 한 연속 구간과 동기화 한 번). 이벤트 묶음마다 저장 한 번, 이미지는 소유자 밖에서 체크포인트. `kill -9`와 커밋 각 단계의 죽음 뒤 확인 응답한 이벤트가 모두 남는다. 레코드·키가 바뀐 모듈로 바꿔도 데이터가 이름으로 옮겨진다 | [076](docs/research/076-one-sync-commit.md), [081](docs/research/081-tail-records.md), [092](docs/research/092-tpcc.md), 008 상태 영속·교체 | | 인터페이스 | 한 명세가 TUI(셀 단위 갱신), CLI, 문장(NUI), 웹 GUI가 된다. 저장하면 실행 중인 앱이 상태를 이어 새 모듈로 바뀐다(`aup watch`, `vega … --watch`) | Vega `docs/design/001-first-component.md`, Vega `make check`(가상 터미널, 헤드리스 Chromium 포함) | diff --git a/docs/design/025-batch-programs.md b/docs/design/025-batch-programs.md index d7f9fd3..c3123b7 100644 --- a/docs/design/025-batch-programs.md +++ b/docs/design/025-batch-programs.md @@ -6,7 +6,10 @@ 10.51 ms(놓인 자리); 막대 ≤ 9.2 ms, ≤ 0.45 µs, ≤ 33 ms에 못 미쳤다. 조각은 중첩 회차의 수단이고, 묶음마다 값은 키로 찾기와 레인 연산의 준비에 있어 이 꼴로는 약 0.6 µs에서 멈춘다. 리스트의 칸 캐시는 3%라 하지 않았다). 다음은 요소마다다(3단계: 4바이트 곱하기, matmul ≤ 21 ms). 4바이트 곱하기 뒤 matmul은 26.57 ms다(명령 −20%). 막대의 셈은 "실수 연산 22 ms 밖은 14 ms 그대로"였는데, 그 밖은 -안쪽 회차마다의 해석 약 15 ms와 행렬 만들기(점화식과 덧붙이기 8만 개) 약 4–5 ms였다: 26.6 ≈ 커널 8 + 회차마다 15 + 만들기 4–5. [024](024-batch-executor.md)가 처음에 적고 만들지 않은 단계("묶음 프로그램은 루프마다 한 번 +안쪽 회차마다의 해석 약 15 ms와 행렬 만들기(점화식과 덧붙이기 8만 개) 약 4–5 ms였다: 26.6 ≈ 커널 8 + 회차마다 15 + 만들기 4–5. 3단계를 +닫았다([136](../research/136-batch-executor-stage-three.md): 곱하기, 레인 없이 시작하는 모으기(sum0 6.09 → 1.01 ms, 막대 ≤ 1.5), +리스트의 칸을 묶음에 한 번; b9 대비 matmul −35%, knapsack −12%, roots −7.6%; 실행기, 은행 질의, TPC-C는 그대로). 다음은 4단계(knapsack의 +훑기 여섯을 셋으로). [024](024-batch-executor.md)가 처음에 적고 만들지 않은 단계("묶음 프로그램은 루프마다 한 번 만든다")이고, [132](../research/132-batch-executor-floor-and-the-way-past.md)의 A, [133](../research/133-register-tiles-measured.md)이 정한 길이다. 사용자의 방향: 범용 장치로, 합친 연산의 표 없이, 기계어 없이, 메모리를 적게(2026-10-05, 2026-10-08). diff --git a/docs/research/136-batch-executor-stage-three.md b/docs/research/136-batch-executor-stage-three.md new file mode 100644 index 0000000..9252469 --- /dev/null +++ b/docs/research/136-batch-executor-stage-three.md @@ -0,0 +1,65 @@ +# 136 — 묶음 실행기 3단계: 4바이트 곱하기, 레인 없이 시작하는 모으기, 리스트의 칸 한 번 + +2026-10-08. [025](../design/025-batch-programs.md)의 3단계다. 요소마다의 값을 연산의 꼴과 폭에 맞춘 루프로 줄였다. 코드는 `5ffae0b` +(4바이트 곱하기), `c74bb65`(레인 없이 시작하는 모으기), `79d016c`(리스트의 칸을 묶음에 한 번)이고, 같은 방법으로 쟀다(`b12`, `b13`, +`b14`; 11번의 중앙값을 번갈아 다섯 번씩, b9와도 세 번씩; 명령 수). + +## 쉬운 말로 + +- **matmul의 막대에 못 미쳤다.** 4바이트 곱하기 뒤 matmul은 26.57 ms다(막대 ≤ 21). 막대의 셈이 실수 연산(약 22 ms) 밖을 14 ms로 두었는데, + 그 밖은 안쪽 회차마다의 해석 약 15 ms와 행렬 만들기 약 4–5 ms였다. 지금 matmul은 커널 약 8 ms + 회차마다 약 14 ms + 만들기 약 + 4–5 ms다. +- **sum0의 막대는 넘었다.** `total = total + 1`의 모으기가 레인을 만들지 않게 하자 sum0이 6.09에서 1.01 ms가 됐다(막대 ≤ 1.5). 명령은 + 85% 줄었다. 이제 sum0의 시간은 거의 묶음마다의 값이다: 묶음 3,907개 × 약 0.25 µs. 세 줄의 블록에 묶음마다 약 1,666 명령이 이 해석기 + 꼴의 바닥이다(레인의 일이 없어진 뒤에 남는 것). +- **b9와 견주면**(같은 조용한 기기, 번갈아): matmul 40.01 → 25.97 ms(−35%, 명령 −26%), knapsack 11.47 → 10.07(−12%, 명령 −5.6%), + roots 8.97 → 8.29(−7.6%, 명령 −7.5%), join 117.2 → 115.8(−1.2%), BFS 24.07 → 24.10, sort 57.0 → 56.8. words는 묶이지 않는 일이고 + 215.4 → 219.2(+1.8%, 놓인 자리의 폭). +- **지키는 것은 지켰다.** 실행기만의 길은 다섯 일 모두 명령 수가 b9와 같다. 은행 질의의 명령 수는 b9와 ±0.08% 안이다. TPC-C(창고 1, + 단말 64, 20초, 번갈아 여섯 번)는 b9 116.3만 대 지금 117.1만 신규 주문/분(+0.7%)이다. + +## 만든 것 + +- **4바이트 곱하기**(`words_op`). 2^32 아래의 정수 레인끼리의 곱이 2^32 아래면 4바이트에 그대로 둔다. 2^32 아래 정수의 곱은 실수의 + 곱과 비트까지 같다. 넘으면(64비트 곱의 위쪽 절반) 더하기처럼 레인을 실수로 돌려 다시 한다. 레인 넷에 `umull`, `umull2`, `uzp1`, + `uzp2`로 명령 10개다. matmul의 곱과 합이 4바이트에 머물러 명령이 20% 줄었다. BFS의 `q.node * 1048576`은 2^32를 넘어 한 번 해 보고 + 실수로 가는데, 명령으로 0.05%다. +- **레인 없이 시작하는 모으기.** 모으기는 레인 배열 없이 수 둘(모든 레인에 같은 부분합과 같은 횟수)로 시작한다. 걸음마다 e가 모든 + 레인에 같은 값이고 가린 레인이 없으면, 각 레인이 할 계산(같은 차례의 같은 연산)을 한 번만 한다. 처음으로 다른 걸음(가린 레인, + 레인마다 다른 e, 고르기, 펼친 걷기)이 오면 그때 레인을 그 수로 채운다. 끝에서는 정수이고 크기가 2^53 아래면 n × 그 수를 더하고(레인의 + 합과 같다), 아니면 회차의 차례대로 접는다. 지금의 검사(정수인지, 2^53, 여러 번 더한 레인)가 그대로다. + - 고정 소스 `REDUCE_SOURCE`를 더했다. 같은 e, 균일한 최대·최소, 분수, 2^53 너머, 중첩 루프 안의 횟수, 같은 e 다음의 가린 걸음과 + 레인마다의 걸음(양쪽 차례)이다. 이 소스가 레인을 그 수로 채우는 길을 56번, 그 수로 접는 길을 77번 지난다. 시드 23의 무작위 + 프로그램은 각각 6번과 53번의 실행에서 지났다. +- **리스트의 칸을 묶음에 한 번**(`cells_of`). `pass`는 리스트를 바꾸지 않는다(grep: 바꾸는 호출 `widen`, `add_many`, `touched`는 + `settle`, 묶음의 끝, 덧붙이기와 걸러내기에만 있다). 그래서 `find`와 `item_get`이 묶음마다 처음 읽는 리스트 넷의 칸을 한 번 가져와 + 쓴다. matmul은 안쪽 회차마다 찾기 둘이라 명령 2.3%, knapsack과 BFS는 0.4%다. 135에서 3%라 미뤘지만 matmul에서는 9%였다. +- **하지 않은 것.** `sweep`(matmul의 회차마다 약 130 사이클)은 1단계부터 블록이 쓰는 지역 변수만 돌고, matmul의 회차는 매번 버퍼를 + 새로 쓰므로 건너뛸 수 없다. 025의 "좁은 열을 4바이트로 바로"는 이미 그렇다(`cells_at`이 1바이트 열을 4바이트 레인으로 읽는다). + +## 잰 것 + +| 일 | b9 | b12 (곱하기) | b13 (모으기) | b14 (칸) | 기계어 | C | +|---|---:|---:|---:|---:|---:|---:| +| matmul | 40.01 ms | 26.56 | 26.76 | **25.97** | 14.2 | 7.6 | +| knapsack | 11.47 | 10.52 | 10.56 | **10.07** | 7.9 | 6.25 | +| roots | 8.97 | 8.82 | 8.31 | **8.29** | 9.57 | 6.86 | +| join | 117.2 | 116.4 | 116.0 | 115.8 | 84.6 | 31.7 | +| BFS | 24.07 | 24.31 | 24.03 | 24.10 | 7.7 | 9.9 | +| sum0 (time.c) | 8.69 | | **1.01** | | | | + +- 실행기만의 join은 한 번의 `icount`에서 사이클이 +11%였는데, 다시 두 번 재니 b9와 ±2% 안이었다(명령은 같다). + +원본: `041-batches/2026-10-08-pairs.jsonl`, `2026-10-08-counts.jsonl`, `040-against-c/2026-10-08-counts.jsonl`(은행 질의), +`2026-10-08-tpcc-*`, `2026-10-08-queries-*`. + +## 뜻과 맞음 + +- 커밋마다 시드 1, 2, 3, 5, 23의 무작위 프로그램(기본과 `PURE_SELECT=all`), 고정 소스의 세 길(두 모드), 단위 시험이 지났다. +- 단계의 끝(`79d016c`와 `REDUCE_SOURCE`)에서 단위 시험 세 모드, ASan 단위 시험(기본과 실행기 모드), sanitized `pure-run`의 고정 소스 + (두 모드)와 시드 23의 프로그램(두 모드), Pure의 `make check`, aup의 검사 두 모드가 지났다. + +## 다음 + +knapsack의 요소마다(약 6 ms, 훑기 여섯)가 이제 스위트에서 손대지 않은 가장 큰 덩어리다. 4단계: 열을 피연산자로 읽기(보폭 읽기가 +레인 배열로 옮기는 훑기 없이), 비교가 가는 레인을 세기(가르기의 세는 훑기 없이). 배낭은 훑기 여섯에서 셋이다. diff --git a/research/experiments/040-against-c/2026-10-08-counts.jsonl b/research/experiments/040-against-c/2026-10-08-counts.jsonl new file mode 100644 index 0000000..9ded043 --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-counts.jsonl @@ -0,0 +1,4 @@ +{"serve": "pure-serve", "per_branch": {"instructions": 27084449, "cycles": 11968165}, "in_credit": {"instructions": 3511883, "cycles": 1642481}, "large": {"instructions": 1419139, "cycles": 694322}, "ranks": {"instructions": 24469168, "cycles": 14816231}, "none": {"instructions": 615600, "cycles": 198839}, "field": {"instructions": 9007132, "cycles": 3270346}, "found": {"instructions": 14139059, "cycles": 10647982}} +{"serve": "pure-serve", "per_branch": {"instructions": 26979581, "cycles": 12079370}, "in_credit": {"instructions": 3488341, "cycles": 1623673}, "large": {"instructions": 1419195, "cycles": 618093}, "ranks": {"instructions": 24411710, "cycles": 15102017}, "none": {"instructions": 615600, "cycles": 199844}, "field": {"instructions": 9007132, "cycles": 3258526}, "found": {"instructions": 14138874, "cycles": 10788782}} +{"serve": "pure-serve", "per_branch": {"instructions": 27066442, "cycles": 11989768}, "in_credit": {"instructions": 3507837, "cycles": 1610192}, "large": {"instructions": 1419139, "cycles": 616080}, "ranks": {"instructions": 24460594, "cycles": 14902801}, "none": {"instructions": 615600, "cycles": 193159}, "field": {"instructions": 9007132, "cycles": 3277228}, "found": {"instructions": 14140402, "cycles": 10893077}} +{"serve": "pure-serve", "per_branch": {"instructions": 27195249, "cycles": 12143448}, "in_credit": {"instructions": 3536801, "cycles": 1672046}, "large": {"instructions": 1419139, "cycles": 612837}, "ranks": {"instructions": 24530686, "cycles": 15174100}, "none": {"instructions": 615600, "cycles": 194135}, "field": {"instructions": 9007235, "cycles": 3279139}, "found": {"instructions": 14137235, "cycles": 10915766}} diff --git a/research/experiments/040-against-c/2026-10-08-load.txt b/research/experiments/040-against-c/2026-10-08-load.txt new file mode 100644 index 0000000..e17ec65 --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-load.txt @@ -0,0 +1,12 @@ +1 s9 16:22:57 up 4 days, 12:44, 2 users, load average: 1.32, 1.34, 1.11 +1 s14 16:24:25 up 4 days, 12:45, 2 users, load average: 1.47, 1.44, 1.17 +2 s14 16:26:01 up 4 days, 12:47, 2 users, load average: 1.35, 1.49, 1.22 +2 s9 16:27:49 up 4 days, 12:49, 2 users, load average: 1.46, 1.55, 1.27 +3 s9 16:29:16 up 4 days, 12:50, 2 users, load average: 1.48, 1.60, 1.32 +3 s14 16:30:53 up 4 days, 12:52, 2 users, load average: 1.37, 1.63, 1.36 +4 s14 16:32:30 up 4 days, 12:53, 2 users, load average: 1.31, 1.60, 1.38 +4 s9 16:34:07 up 4 days, 12:55, 2 users, load average: 1.32, 1.60, 1.41 +5 s9 16:35:34 up 4 days, 12:56, 2 users, load average: 1.34, 1.58, 1.42 +5 s14 16:37:01 up 4 days, 12:58, 2 users, load average: 1.46, 1.64, 1.46 +6 s14 16:38:48 up 4 days, 13:00, 2 users, load average: 1.33, 1.67, 1.50 +6 s9 16:40:15 up 4 days, 13:01, 2 users, load average: 1.37, 1.65, 1.51 diff --git a/research/experiments/040-against-c/2026-10-08-queries-s14-1.jsonl b/research/experiments/040-against-c/2026-10-08-queries-s14-1.jsonl new file mode 100644 index 0000000..8ab0066 --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-queries-s14-1.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.32, "pure_fastest_ms": 5.25, "sqlite_median_ms": 44.93, "sqlite_fastest_ms": 44.85, "sqlite_indexed_median_ms": 14.11, "sqlite_indexed_fastest_ms": 14.05} +{"query": "in_credit", "rows": 1, "accounts": 100000, "pure_median_ms": 0.83, "pure_fastest_ms": 0.8, "sqlite_median_ms": 5.9, "sqlite_fastest_ms": 5.87, "sqlite_indexed_median_ms": 0.16, "sqlite_indexed_fastest_ms": 0.16} +{"query": "large", "rows": 212, "accounts": 100000, "pure_median_ms": 0.38, "pure_fastest_ms": 0.35, "sqlite_median_ms": 1.48, "sqlite_fastest_ms": 1.47, "sqlite_indexed_median_ms": 1.48, "sqlite_indexed_fastest_ms": 1.47} +{"query": "ranks", "rows": 404, "accounts": 100000, "pure_median_ms": 6.77, "pure_fastest_ms": 6.7, "sqlite_median_ms": 2842.0, "sqlite_fastest_ms": 2838.67, "sqlite_indexed_median_ms": 7.55, "sqlite_indexed_fastest_ms": 7.5} diff --git a/research/experiments/040-against-c/2026-10-08-queries-s14-2.jsonl b/research/experiments/040-against-c/2026-10-08-queries-s14-2.jsonl new file mode 100644 index 0000000..28b485a --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-queries-s14-2.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.31, "pure_fastest_ms": 5.2, "sqlite_median_ms": 45.25, "sqlite_fastest_ms": 45.09, "sqlite_indexed_median_ms": 14.0, "sqlite_indexed_fastest_ms": 13.96} +{"query": "in_credit", "rows": 1, "accounts": 100000, "pure_median_ms": 0.85, "pure_fastest_ms": 0.82, "sqlite_median_ms": 5.89, "sqlite_fastest_ms": 5.86, "sqlite_indexed_median_ms": 0.16, "sqlite_indexed_fastest_ms": 0.16} +{"query": "large", "rows": 212, "accounts": 100000, "pure_median_ms": 0.37, "pure_fastest_ms": 0.35, "sqlite_median_ms": 1.49, "sqlite_fastest_ms": 1.47, "sqlite_indexed_median_ms": 1.5, "sqlite_indexed_fastest_ms": 1.47} +{"query": "ranks", "rows": 404, "accounts": 100000, "pure_median_ms": 6.89, "pure_fastest_ms": 6.79, "sqlite_median_ms": 2841.84, "sqlite_fastest_ms": 2838.85, "sqlite_indexed_median_ms": 7.61, "sqlite_indexed_fastest_ms": 7.53} diff --git a/research/experiments/040-against-c/2026-10-08-queries-s14-3.jsonl b/research/experiments/040-against-c/2026-10-08-queries-s14-3.jsonl new file mode 100644 index 0000000..37c986b --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-queries-s14-3.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.25, "pure_fastest_ms": 5.18, "sqlite_median_ms": 45.25, "sqlite_fastest_ms": 45.17, "sqlite_indexed_median_ms": 14.02, "sqlite_indexed_fastest_ms": 13.96} +{"query": "in_credit", "rows": 1, "accounts": 100000, "pure_median_ms": 0.85, "pure_fastest_ms": 0.81, "sqlite_median_ms": 5.89, "sqlite_fastest_ms": 5.87, "sqlite_indexed_median_ms": 0.16, "sqlite_indexed_fastest_ms": 0.16} +{"query": "large", "rows": 212, "accounts": 100000, "pure_median_ms": 0.38, "pure_fastest_ms": 0.35, "sqlite_median_ms": 1.48, "sqlite_fastest_ms": 1.47, "sqlite_indexed_median_ms": 1.48, "sqlite_indexed_fastest_ms": 1.47} +{"query": "ranks", "rows": 404, "accounts": 100000, "pure_median_ms": 6.85, "pure_fastest_ms": 6.75, "sqlite_median_ms": 2845.71, "sqlite_fastest_ms": 2840.64, "sqlite_indexed_median_ms": 7.61, "sqlite_indexed_fastest_ms": 7.52} diff --git a/research/experiments/040-against-c/2026-10-08-queries-s14-4.jsonl b/research/experiments/040-against-c/2026-10-08-queries-s14-4.jsonl new file mode 100644 index 0000000..1b0f465 --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-queries-s14-4.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.35, "pure_fastest_ms": 5.22, "sqlite_median_ms": 45.23, "sqlite_fastest_ms": 45.13, "sqlite_indexed_median_ms": 14.1, "sqlite_indexed_fastest_ms": 14.03} +{"query": "in_credit", "rows": 1, "accounts": 100000, "pure_median_ms": 0.89, "pure_fastest_ms": 0.82, "sqlite_median_ms": 5.89, "sqlite_fastest_ms": 5.87, "sqlite_indexed_median_ms": 0.16, "sqlite_indexed_fastest_ms": 0.16} +{"query": "large", "rows": 212, "accounts": 100000, "pure_median_ms": 0.38, "pure_fastest_ms": 0.35, "sqlite_median_ms": 1.49, "sqlite_fastest_ms": 1.47, "sqlite_indexed_median_ms": 1.48, "sqlite_indexed_fastest_ms": 1.47} +{"query": "ranks", "rows": 404, "accounts": 100000, "pure_median_ms": 6.83, "pure_fastest_ms": 6.78, "sqlite_median_ms": 2843.8, "sqlite_fastest_ms": 2840.72, "sqlite_indexed_median_ms": 7.61, "sqlite_indexed_fastest_ms": 7.51} diff --git a/research/experiments/040-against-c/2026-10-08-queries-s14-5.jsonl b/research/experiments/040-against-c/2026-10-08-queries-s14-5.jsonl new file mode 100644 index 0000000..5a42b6c --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-queries-s14-5.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.25, "pure_fastest_ms": 5.19, "sqlite_median_ms": 45.23, "sqlite_fastest_ms": 45.16, "sqlite_indexed_median_ms": 14.11, "sqlite_indexed_fastest_ms": 14.05} +{"query": "in_credit", "rows": 1, "accounts": 100000, "pure_median_ms": 0.87, "pure_fastest_ms": 0.82, "sqlite_median_ms": 5.9, "sqlite_fastest_ms": 5.88, "sqlite_indexed_median_ms": 0.16, "sqlite_indexed_fastest_ms": 0.16} +{"query": "large", "rows": 212, "accounts": 100000, "pure_median_ms": 0.37, "pure_fastest_ms": 0.35, "sqlite_median_ms": 1.49, "sqlite_fastest_ms": 1.47, "sqlite_indexed_median_ms": 1.49, "sqlite_indexed_fastest_ms": 1.47} +{"query": "ranks", "rows": 404, "accounts": 100000, "pure_median_ms": 6.82, "pure_fastest_ms": 6.71, "sqlite_median_ms": 2842.74, "sqlite_fastest_ms": 2840.54, "sqlite_indexed_median_ms": 7.59, "sqlite_indexed_fastest_ms": 7.52} diff --git a/research/experiments/040-against-c/2026-10-08-queries-s14-6.jsonl b/research/experiments/040-against-c/2026-10-08-queries-s14-6.jsonl new file mode 100644 index 0000000..34ee9bf --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-queries-s14-6.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.27, "pure_fastest_ms": 5.23, "sqlite_median_ms": 45.48, "sqlite_fastest_ms": 45.29, "sqlite_indexed_median_ms": 14.07, "sqlite_indexed_fastest_ms": 14.06} +{"query": "in_credit", "rows": 1, "accounts": 100000, "pure_median_ms": 0.91, "pure_fastest_ms": 0.83, "sqlite_median_ms": 5.91, "sqlite_fastest_ms": 5.87, "sqlite_indexed_median_ms": 0.16, "sqlite_indexed_fastest_ms": 0.16} +{"query": "large", "rows": 212, "accounts": 100000, "pure_median_ms": 0.49, "pure_fastest_ms": 0.41, "sqlite_median_ms": 1.53, "sqlite_fastest_ms": 1.48, "sqlite_indexed_median_ms": 1.48, "sqlite_indexed_fastest_ms": 1.47} +{"query": "ranks", "rows": 404, "accounts": 100000, "pure_median_ms": 6.77, "pure_fastest_ms": 6.68, "sqlite_median_ms": 2841.65, "sqlite_fastest_ms": 2838.36, "sqlite_indexed_median_ms": 7.61, "sqlite_indexed_fastest_ms": 7.53} diff --git a/research/experiments/040-against-c/2026-10-08-queries-s9-1.jsonl b/research/experiments/040-against-c/2026-10-08-queries-s9-1.jsonl new file mode 100644 index 0000000..1892a39 --- /dev/null +++ b/research/experiments/040-against-c/2026-10-08-queries-s9-1.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.22, "pure_fastest_ms": 5.13, "sqlite_median_ms": 45.97, "sqlite_fastest_ms": 44.91, 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b/research/experiments/040-against-c/2026-10-08-queries-s9-2.jsonl @@ -0,0 +1,4 @@ +{"query": "per_branch", "rows": 10, "accounts": 100000, "pure_median_ms": 5.28, "pure_fastest_ms": 5.18, "sqlite_median_ms": 45.47, "sqlite_fastest_ms": 45.23, "sqlite_indexed_median_ms": 14.09, "sqlite_indexed_fastest_ms": 14.04} +{"query": "in_credit", "rows": 1, "accounts": 100000, "pure_median_ms": 0.84, "pure_fastest_ms": 0.8, "sqlite_median_ms": 5.89, "sqlite_fastest_ms": 5.87, "sqlite_indexed_median_ms": 0.16, "sqlite_indexed_fastest_ms": 0.16} +{"query": "large", "rows": 212, "accounts": 100000, "pure_median_ms": 0.38, "pure_fastest_ms": 0.35, "sqlite_median_ms": 1.48, "sqlite_fastest_ms": 1.47, "sqlite_indexed_median_ms": 1.48, "sqlite_indexed_fastest_ms": 1.46} +{"query": "ranks", "rows": 404, "accounts": 100000, "pure_median_ms": 6.66, "pure_fastest_ms": 6.6, "sqlite_median_ms": 2841.94, "sqlite_fastest_ms": 2837.62, "sqlite_indexed_median_ms": 7.58, "sqlite_indexed_fastest_ms": 7.51} diff 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