documenting smp and scheduling to research
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@ -57,6 +57,9 @@ Cutting across all of these:
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- **[discovery.md](discovery.md) — device discovery.** A design note (not built yet)
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on learning what hardware exists via ACPI (x86) or device tree (ARM) behind one
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neutral device model — when to build it, and how to keep it architecture-agnostic.
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- **[smp.md](smp.md) — multiple cores.** A design/research note on how microkernels
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(L4, seL4) handle SMP — big kernel lock vs per-CPU vs multikernel — and how the
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right choice depends on whether danos is chasing real-time or resilience.
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- **[sysv.md](sysv.md) — the calling convention.** What "the kernel is SysV" means,
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and why the loader→kernel boundary has to pin it (the RDI-vs-RCX handoff).
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- **[testing.md](testing.md) — testing.** How the kernel is tested by booting it in
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# SMP: multiple cores, the microkernel way
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A design/research note, not built yet. danos runs on **one core** today (see
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[scheduling.md](scheduling.md)); this maps how microkernels — especially the L4
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family and seL4 — handle **symmetric multiprocessing (SMP)**, so the eventual port
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has a plan and a reading list. It also flags where those choices depend on whether
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danos is chasing **real-time** or **resilience** (see the note at the end).
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## First, the vocabulary
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Three independent things people conflate (see [scheduling.md](scheduling.md) for the
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danos specifics):
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- **Task capacity** (`max_tasks`) — how many tasks can *exist*. A table size.
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- **Cores** — how many tasks *run at the same instant*. One running task per core.
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- **Real-time** — whether timing is *predictable*. Comes from bounded operations
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(our O(1) scheduler), not from core count.
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danos is uniprocessor today: one global `current` task, one set of ready queues, one
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timer. Even on an 8-core CPU, the firmware starts only the **bootstrap processor
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(BSP)**; the other cores (**application processors**, APs) sit parked until the
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kernel wakes them, which it doesn't yet.
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## The common microkernel instinct: don't share kernel state
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Monolithic kernels (Linux) share large amounts of state across cores behind many
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fine-grained locks. Microkernels lean the other way — the kernel does *little* (IPC,
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scheduling, capabilities), so the pressure is to make kernel state **per-core** and
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coordinate cores with **inter-processor interrupts (IPIs) or messages** rather than
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shared, locked data structures. Two hallmarks follow:
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- **Thread-to-core affinity.** Threads are usually *bound* to a core; migration is an
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explicit operation, not automatic load-balancing.
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- **Policy in user space.** *Which* core a thread runs on tends to be a user-level
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decision (a scheduler/manager server); the kernel just provides the mechanism to
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run it there and to signal across cores. This matches the microkernel creed:
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mechanism in the kernel, policy outside.
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Within that instinct, the L4 family split on **how much to lock**.
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## seL4: the "big kernel lock" — and why it's not a hack
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seL4's choice is striking: a **single big kernel lock (BKL)**. Only one core runs
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*kernel* code at a time; **user code runs fully in parallel** on all cores. A core
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that traps into the kernel takes the global lock, does its (short) work, releases it.
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Why so coarse? **Formal verification.** seL4's whole value is a machine-checked
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correctness proof, built for a *uniprocessor* kernel — reasoning about one thread of
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kernel execution. Fine-grained SMP locking explodes the interleavings you'd have to
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reason about. The big lock **serialises kernel execution so the single-core reasoning
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still holds**. It trades kernel scalability for verifiability.
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And it works better than it sounds, *because the kernel does so little*: the lock is
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held for short, bounded intervals, while the real work (drivers, services) runs in
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user space in parallel, outside the lock. Scheduling is otherwise **per-core** (each
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core its own ready queues), threads carry an **affinity**, and cross-core IPC costs an
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IPI.
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> Nuance: the fully *verified* seL4 configuration is the uniprocessor one. The
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> SMP/big-lock version isn't covered by the same end-to-end proof — extending
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> verification to multicore has been ongoing research. So the big lock is partly
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> "stay close to the thing we proved."
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seL4 also layers **MCS** (mixed-criticality scheduling) on top: **scheduling
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contexts** carrying a time *budget* and *period*, so a thread can't overrun its share
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— temporal isolation, reasoned about per core. This is the seriously real-time part.
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## Fiasco.OC / NOVA: per-CPU, finer-grained
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Not all L4s took the big lock. **Fiasco.OC** (TU Dresden L4, part of L4Re) is
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**per-CPU**: per-CPU run queues, CPU-local kernel objects, IPIs for the rare
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cross-CPU operations. Threads bind to a CPU; moving one is explicit. Scales better
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than a big lock, more complex, and without seL4's verification constraint forcing the
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issue. **NOVA** (a microhypervisor) is similarly per-CPU. The shared pattern: make
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everything CPU-local you can, and when cores must interact, **send a message/IPI**
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instead of touching shared data.
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## The extreme: the "multikernel"
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Taken to its logical end you get **Barrelfish** (ETH Zurich): treat a multicore
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machine as a *network of cores*, each running its **own kernel instance**, sharing
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**no** kernel memory, communicating **only by message passing** — the microkernel's
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IPC philosophy applied to the kernel's own structure. seL4's "clustered multikernel"
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explorations use the same idea: groups of cores, each cluster a big-lock domain,
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clusters talking by messages. The insight: if you're already committed to messages
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for user-space isolation, structure the kernel across cores the same way and sidestep
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shared-memory locking entirely.
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## Does the right choice depend on real-time vs resilience?
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Yes — and this is the branch that matters for danos right now.
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- **If the goal is hard real-time:** favour **per-core scheduling with fixed
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affinity**. A thread never gets surprise-migrated mid-deadline, and each core's
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timeline can be reasoned about in isolation. Global load-balancing (Linux's default)
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is great for throughput and *bad* for determinism, which is why RT microkernels
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mostly pin threads. seL4's MCS scheduling contexts are the reference model.
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- **If the goal is resilience / restartability:** the SMP priority shifts to **fault
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isolation and recovery**, not timing. What matters is that a failed component (a
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driver, a service) on any core can be **killed and restarted** without taking the
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system down — which is a property of address-space isolation + a supervising
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restart server (below), *largely orthogonal to how cores are scheduled*. A big lock
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is perfectly fine here; you're optimising for "a crash is contained and
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recoverable," not "latency is bounded to N µs."
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- **If the goal is throughput:** you'd care about lock contention and per-core
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queues — the least microkernel-flavoured of the three.
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These pull in different directions, so **picking the primary goal comes before
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picking the SMP design.** (danos's founding assumption was real-time; that's under
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active reconsideration in favour of resilience — see [vision.md](vision.md).)
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## What this would mean for danos
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Whatever the top goal, the *sequence* is the same and seL4 validates starting simple:
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1. **Enumerate cores** — needs [device discovery](discovery.md) (ACPI MADT on x86,
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device tree on ARM). SMP is a concrete consumer of that work.
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2. **Wake the APs** — INIT–SIPI–SIPI on x86; PSCI/spin-tables on ARM. Each core brings
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up its own tables, timer, and idle task.
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3. **Start with a big kernel lock.** It's a legitimate first design, not a shortcut —
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philosophically aligned with a tiny kernel, and it lets the single-core correctness
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model you already have (the interrupt-flag discipline in
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[scheduling.md](scheduling.md)) stay largely intact: one lock around kernel entry
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instead of rethinking every critical section.
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4. **Later, if contention bites,** evolve toward **per-core run queues + explicit
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affinity** (the Fiasco.OC direction) — also the more real-time-predictable model.
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5. **Placement stays a user-space policy** — the kernel runs a thread on the core it's
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told to, a user-level manager decides which.
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Big-lock-first → per-core-later. The affinity/MCS depth is only worth it if real-time
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turns out to be the actual goal.
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## Further reading
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**Microkernel SMP & scheduling**
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- Klein et al., *"seL4: Formal Verification of an OS Kernel"* (SOSP 2009) — the
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verification that shapes seL4's whole SMP stance.
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- Lyons et al., *"Scheduling-Context Capabilities: A Principled, Light-Weight OS
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Mechanism for Managing Time"* (EuroSys 2018) — seL4 MCS, the real-time model.
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- The **seL4 whitepaper** and "towards a verified multiprocessor seL4" material — the
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big-lock / clustered-multikernel reasoning.
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- **Fiasco.OC / L4Re** documentation (TU Dresden) — the per-CPU alternative.
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- Baumann et al., *"The Multikernel: A New OS Architecture for Scalable Multicore
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Systems"* (SOSP 2009) — Barrelfish, the share-nothing extreme.
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**Resilience / self-healing (if that's the real goal)**
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- Herder et al., *"Fault Isolation for Device Drivers"* and the **MINIX 3**
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*reincarnation server* — a driver crashes, a supervisor restarts it live. The
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closest existing system to "re-initialise parts of the OS."
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- **QNX** — commercial microkernel RTOS built on message passing and restartable
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drivers; good study of the combination.
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- **Erlang/OTP** *supervision trees* and the *"let it crash"* philosophy — not a
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kernel, but the canonical design for "isolate failures and restart the failed
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part," directly relevant to danos's restartability motivation.
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## Related
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- [scheduling.md](scheduling.md) — the single-core scheduler SMP would extend.
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- [discovery.md](discovery.md) — enumerating cores is a device-discovery problem.
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- [ipc.md](ipc.md) — the message passing cross-core coordination rides on.
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- [vision.md](vision.md) — the goals question (real-time vs resilience) this note
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keeps bumping into.
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@ -18,8 +18,8 @@ const heap = @import("heap.zig");
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pub const Priority = u3;
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const num_priorities = 8;
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const stack_size = 16 * 1024; // per-task kernel stack
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const max_tasks = 16;
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const stack_size = 16 * 1024; // each task's kernel stack is 16 KiB
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const max_tasks = 16; // the maximum number of tasks alive at once is 16 in a static sized pool
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const State = enum { free, ready, running, blocked };
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