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* Watch a subscriber for writing only while it keeps output, and measure ↵eunhhu2026-10-041-0/+1
| | | | freshness by push and polling (019)
* Measure a link at rest: 132 bytes against a QUIC connection's 38,106 (094)eunhhu2026-09-281-0/+1
| | | | | | | | | | | | | | | | | M1 of design 011. A Pure node allows 1,000 to 1,000,000 senders; each sends one order and, once told it is stored, rests. At rest a link costs the node 132 bytes (the sender allowed, 73; its number heard, about 60) and no transport state; with a million the node runs in 139 MB. A quinn 0.11 service holding the same exchange's clients connected at rest costs 38,106 bytes a connection: 289 times as much, past the design's 1/100. A link at rest takes its next record in 0.56 ms to stored, one X25519 on the node included; a new QUIC connection takes 1.06 ms and 2.8 times the receiver's CPU, without storing. research/experiments/019-idle-links: links.c, many senders written from serve/link.h's packet format alone (a second implementation), and the quinn service and clients (quic/, built offline); run.py makes both measurements.
* Run pgbench's transaction on a bank of 100,000 accounts, beside SQLite (090)eunhhu2026-09-271-0/+1
| | | | | | | | | | | | | | | | | benchmarks/bank/bank.aup keeps accounts, tellers and branches as keyed lists and a history list; a transfer changes a row of each and appends a history row in one event, as pgbench's TPC-B-like transaction does in SQL. run.py makes a scale's rows and drives transfers through the load generator's new transfer kind; sqlite-bank.c runs the same tables and SQL on SQLite 3.46.1, a connection a thread, WAL. With lists as trees, transfers run at 30.5k a second on 1,000 accounts and 24.5k on 100,000 (RAM store, one connection thread, HTTP and JSON included), where they ran at 3.2k on 30,000 before. Durable on the SD card, Pure makes 1,339 a second and SQLite with synchronous=FULL 84 to 153. SQLite in process with no HTTP makes about 40k in RAM: recorded as it is, with the write amplification of 100,000-row tables on the card and ad hoc queries as what comes next.
* Add a sampling profiler for machines without perfeunhhu2026-09-271-0/+1
| | | | | | | | | | | | benchmarks/sample.c runs a command and samples where its threads spend user time (the task clock every 50 us, one perf_event_open event a CPU, since the kernel maps no ring for an inherited per-task event), then names the samples from the ELF symbol tables of the files the command had mapped: a stripped library from its debug file by build id. On arm64 it also takes the link register, so time in a library's leaf (memcpy, strcmp) is shown again by its caller. The command's user and system time head the report.
* Lay Pure out as a core with the parts selected around iteunhhu2026-09-271-0/+1
| | | | | | | | | | | | | | | | | | | | | The app model, the tree store and the HTTP host lived in prototypes/connections among the earlier document runtime, the store was known only by its format's name, and Vega compiled six Pure sources by path. Now, as the README's principle has it: core/ runtime, flow and the app model (module*.c), with what the core asks of storage (state.h, store.h) store/ the tree store (PURETRE3, PUREREC1) serve/ pure-serve: HTTP host, outbound delivery, JSON in place cli/ pure-run, pure-edit-module A top-level make builds libpure.a (app model and store, for hosts to link) and the hosts; make check runs the store's and the app model's tests. The earlier runtime still builds from prototypes/connections against core/ and store/ (check, check-tree and check-core pass). Design 009 records the rule: parts by role behind libraries; git repositories split by coupling, so the store stays here while its contract moves with the core, and Vega stays apart.
* Benchmark an app served by its views and inputseunhhu2026-09-261-0/+1
| | | | | | | | | | run.py --suite app serves the scoreboard of scores.aup (22 lines of aup) with pure-serve against the same scoreboard written by hand in axum and drogon: POST /inputs/score?points=N with a name as the body, GET /views/total and a page of 20 rows as JSON. Durable, the baselines append each score to a log and fdatasync it before answering (replayed at start); the load generator learns the three requests.
* Benchmark the HTTP hosts against axumeunhhu2026-09-261-0/+2
| | | | | | | | | | | | A C load generator, an axum service with the same document contract (in memory, fdatasync, and crash-safe replacement), and a runner that pins the servers and the load to separate CPUs. On the Pi 5, Pure uses about 40% less memory, wins with a new connection per request and with eight durable writers (3.2x the crash-safe axum), but loses 5x on keep-alive reads and 1.5x on 64 durable writers: no persistent connections, one thread, eight connection slots and two fsyncs per commit. Note 075 records the numbers and the targets.
* Establish native micro runtime checkpointeunhhu2026-09-241-0/+7