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Paper Reference Document

Hollywood Squares OS: A Coordination Operating System for Verified Compositional Intelligence

Complete reference for paper authors

Table of Contents

  1. Core Thesis and Claims
  2. Abstract Drafts
  3. Key Vocabulary
  4. Architecture Details
  5. The Bubble Machine
  6. Experimental Results
  7. Theorems and Proofs
  8. Code Examples
  9. Trace Examples
  10. Comparisons
  11. Historical Context
  12. Figures and Diagrams
  13. Key Sentences
  14. Related Work
  15. Future Work
  16. Appendices

Core Thesis and Claims

The Thesis

Structure is meaning.

The wiring determines the behavior. The messages carry the computation. The trace tells the story.

The Main Result

Deterministic message passing + bounded local semantics + enforced observability ⇒ global convergence with inherited correctness.

This is not about sorting. This is about how correctness scales.

The Hypothesis (Validated)

Learned, verified micro-processors can be composed into distributed systems where the topology carries the algorithm, every step is deterministic, and correctness propagates from parts to whole.

What We Proved

  1. Topology IS the Algorithm — Same handlers + different wiring = different behavior
  2. The Bus IS the Computer — Messages aren't infrastructure, they're computation
  3. Correctness Propagates — Verified handlers + deterministic composition = verified system
  4. Single-Step Enables Trust — Observation replaces archaeology
  5. Replay Enables Verification — Any execution can be exactly reproduced

Abstract Drafts

Short Abstract (150 words)

We present Hollywood Squares OS, a distributed microkernel for addressable processor networks where message passing serves as the syscall interface. Unlike traditional operating systems that manage resources, Hollywood Squares OS manages meaning—coordinating causality, message order, and semantic execution. We demonstrate that deterministic message passing combined with bounded local semantics and enforced observability yields global convergence with inherited correctness. Our flagship demonstration, the Bubble Machine, proves distributed convergence under strict observability constraints: a computational field that relaxes toward order through local compare-swap operations, fully traceable and deterministically replayable. The system achieves verified compositional intelligence: small correct parts compose into larger systems where correctness propagates. We provide complete implementation, specification, and experimental validation.

Extended Abstract (250 words)

We present Hollywood Squares OS, a distributed microkernel designed for addressable processor networks where message passing serves as the fundamental syscall interface. Unlike traditional operating systems that manage computational resources (CPU time, memory, I/O bandwidth), Hollywood Squares OS manages meaning—coordinating causality, message order, and semantic execution across a field of verified processors.

We introduce the concept of a coordination OS: a system that coordinates meaning flow rather than resource allocation. The architecture consists of three cleanly separated layers: a computational substrate (nodes, messages, deterministic ticks), a kernel contract (mailbox, dispatcher, handlers, replay), and a cognitive layer (fields, waves, relaxation algorithms).

Our main theoretical contribution is demonstrating that deterministic message passing + bounded local semantics + enforced observability ⇒ global convergence with inherited correctness. This changes the equation for distributed systems: instead of verifying correctness post-hoc, we construct it by design.

We validate this with the Bubble Machine: a computational field that relaxes toward order through local compare-swap operations. With no shared memory, no global control, and only local rules communicated via messages, the field converges to sorted order in O(n) cycles. Every comparison is traceable; every execution is deterministically replayable.

The system achieves what we call verified compositional intelligence: the composition of small, correct parts into larger systems where correctness propagates from components to the whole. We provide a complete implementation (3,600 lines), formal specification, and reproducible experimental validation.

Key Vocabulary

Must Use Consistently

Term Definition
Coordination OS An OS that manages meaning (causality, message order, semantic execution) rather than resources
Message with meaning The fundamental primitive: a 16-byte frame carrying typed, addressed, meaningful content
Topology is the algorithm Same handlers + different wiring = different global behavior
Bus is the computer Computation happens through messages, not despite them
Deterministic replay Any execution can be exactly reproduced from its trace
Verified compositional intelligence Correct parts compose into correct wholes
Bubble Machine Flagship demo: computational field that relaxes toward order
Node kernel The kernel running on each node (mailbox, dispatcher, handlers)
Fabric kernel Services running on master (directory, router, supervisor, tracer)

Avoid

Don't Say Say Instead
"Neural network" "Verified handlers" or "learned primitives"
"AI" "Compositional intelligence" or "semantic computation"
"Process" "Node" or "handler"
"File" "Message" or "state"
"Scheduler" "Phase scheduler" or "coordinator"

Architecture Details

System Overview

┌─────────────────────────────────────────────────────────────┐
│                      MASTER (Node 0)                        │
│  ┌───────────────────────────────────────────────────────┐  │
│  │                   FABRIC KERNEL                       │  │
│  │  Directory │ Router │ Supervisor │ Loader │ Tracer    │  │
│  └───────────────────────────────────────────────────────┘  │
│  ┌───────────────────────────────────────────────────────┐  │
│  │                   NODE KERNEL                         │  │
│  │  Mailbox │ Dispatcher │ Scheduler │ Memory │ Timers   │  │
│  └───────────────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────────────┘
                              │
        ┌─────────┬─────────┬─┴─┬─────────┬─────────┐
        ▼         ▼         ▼   ▼         ▼         ▼
   ┌────────┐┌────────┐┌────────┐┌────────┐┌────────┐
   │Worker 1││Worker 2││Worker 3││Worker 4││  ...   │
   │  NODE  ││  NODE  ││  NODE  ││  NODE  ││  NODE  │
   │ KERNEL ││ KERNEL ││ KERNEL ││ KERNEL ││ KERNEL │
   └────────┘└────────┘└────────┘└────────┘└────────┘

Three-Layer Model

Layer Name Components Role
1 Computational Substrate Nodes, messages, ticks The physics
2 Kernel Contract Mailbox, dispatcher, handlers, replay The OS
3 Cognitive Layer Fields, waves, relaxation The intelligence

Message Frame Format

┌────────┬────────┬────────┬────────┬────────┬────────┬─────────────┐
│  Type  │   ID   │  Src   │  Dst   │  Len   │ Flags  │   Payload   │
│ 1 byte │ 1 byte │ 1 byte │ 1 byte │ 1 byte │ 1 byte │  10 bytes   │
└────────┴────────┴────────┴────────┴────────┴────────┴─────────────┘
                         Total: 16 bytes

Message Types

Code Type Purpose
0x01 PING Health check request
0x02 PONG Health check response
0x03 EXEC Execute operation
0x04 EXEC_OK Operation succeeded
0x05 EXEC_ERR Operation failed
0x0A RESET Reset node
0x0B TRACE Log event
0x0F HALT Stop node
0x20 GET Get value (Bubble Machine)
0x21 SET Set value (Bubble Machine)
0x22 CSWAP Compare-swap (Bubble Machine)

Node Kernel Components

Component Function
Mailbox Bounded message queues (16 deep)
Dispatcher Routes messages to handlers by type
Handlers Registered operations (extensible)
Memory 64KB local address space
Tick counter Deterministic time

Fabric Kernel Services

Service Function
Directory Node registry, status tracking
Router Load-aware work distribution
Supervisor Health monitoring, heartbeat, restart
Loader Program deployment
Tracer Event logging, replay support

Key Properties

Property Description
Determinism Same initial state + same messages = same result
Observability Every message logged, every state recorded
Replayability Any execution reproduced from trace
Compositionality Verified parts compose into verified wholes

The Bubble Machine

Definition

A Bubble Machine is a tuple (N, T, H, φ) where:

  • N = set of nodes, each holding a value
  • T = topology defining neighbor relationships
  • H = set of handlers (GET, SET, CSWAP)
  • φ = phase schedule over node pairs

Handlers

Handler Input Output Semantics
GET — value Return current value
SET value ack Store value in memory
CSWAP neighbor_val, direction (my_val, swapped) Compare-swap with neighbor

Handler Properties

Each handler is:

  • Bounded: Finite input space (8-bit values)
  • Deterministic: Same input → same output
  • Verifiable: Can be exhaustively tested (256² = 65,536 cases for CSWAP)

Phase Schedule (Line Topology)

EVEN phase: compare pairs (1,2), (3,4), (5,6), (7,8)
ODD phase:  compare pairs (2,3), (4,5), (6,7)

This is odd-even transposition sort via message passing.

Phase Schedule (Grid Topology)

H-EVEN: Horizontal pairs at even columns
H-ODD:  Horizontal pairs at odd columns
V-EVEN: Vertical pairs at even rows
V-ODD:  Vertical pairs at odd rows

Convergence

For line topology with n nodes:

  • Worst case: n cycles to convergence
  • Each cycle: Moves maximum unsorted element ≥1 position toward final location
  • Termination: Detected by zero swaps in a complete cycle (quiescence)

What Makes It Significant

The Bubble Machine demonstrates:

  • ✓ No shared memory
  • ✓ No global control
  • ✓ Only local rules
  • ✓ Only messages
  • ✓ Convergence to sorted order
  • ✓ Full traceability
  • ✓ Deterministic replay

"This is a proof of distributed convergence under strict observability constraints."

Experimental Results

System Configuration

Parameter Value
Topology 1 master + 8 workers (star)
Implementation Python 3.12
Message frame 16 bytes
Node memory 64KB per node
Mailbox depth 16 messages

Bubble Machine Results (Default Test Case)

Input: [64, 25, 12, 22, 11, 90, 42, 7]

Output: [7, 11, 12, 22, 25, 42, 64, 90]

Metric Value
Cycles to convergence 4-5
Total swaps 18
Total events 28-35
Total ticks 450-510
Messages delivered 310-350
Final sorted True

Cycle-by-Cycle Progression

Cycle Values Swaps Status
0 [64, 25, 12, 22, 11, 90, 42, 7] 0 Initial
1 [25, 12, 64, 11, 22, 7, 90, 42] 5 Flowing
2 [12, 11, 25, 7, 64, 22, 42, 90] 6 Flowing
3 [11, 7, 12, 22, 25, 42, 64, 90] 6 Flowing
4 [7, 11, 12, 22, 25, 42, 64, 90] 1 Settled
5 [7, 11, 12, 22, 25, 42, 64, 90] 0 Quiescent

Messages Per Operation

Operation Messages
Load 8 values 16 (8 SET + 8 ACK)
One GET 2 (request + response)
One CSWAP 2-4 (request + response, possibly SET)
One cycle ~30-40

Theorems and Proofs

Theorem 1: Determinism

Statement: Given identical initial state S₀ and message sequence M, execution produces identical final state Sf.

Proof sketch:

  1. Each handler is a pure function: input → output
  2. Message delivery order is deterministic (FIFO per channel)
  3. Tick-by-tick execution is sequential within each node
  4. Therefore, state evolution is uniquely determined by S₀ and M. ∎

Theorem 2: Bubble Machine Convergence

Statement: A Bubble Machine with n nodes in line topology converges to sorted order in at most n cycles.

Proof sketch:

  1. Define inversion count I = number of pairs (i,j) where i < j but value[i] > value[j]
  2. Each swap reduces I by at least 1
  3. I starts at most n(n-1)/2
  4. Each cycle performs at least one swap if I > 0
  5. After at most n cycles, I = 0 (sorted) ∎

Theorem 3: Correctness Propagation

Statement: If each handler h ∈ H satisfies specification Spec(h), then the composed system satisfies Spec(system).

Proof sketch:

  1. System behavior is sequence of handler invocations
  2. Each invocation produces correct output (by assumption)
  3. Message passing preserves message content (no corruption)
  4. Deterministic composition of correct steps yields correct result ∎

Lemma: Replay Correctness

Statement: replay(trace(execution)) produces identical state sequence.

Proof: Follows directly from Theorem 1 (Determinism). The trace captures the complete message sequence; replaying it reproduces the execution. ∎

Code Examples

Creating the System

from hsquares_os import HSquaresOS, BubbleMachine

# Create 1×8 system
os = HSquaresOS(num_workers=8)
os.boot()  # Returns {1: True, 2: True, ..., 8: True}

Basic Operations

# Execute operation on specific node
result = os.exec(node=1, op=OpCode.ADD, a=50, b=10)
# Returns (60, 0)  # (result, carry)

# Route to best available node
result = os.route(op=OpCode.ADD, a=100, b=55)
# Returns (node_id, result, extra)

# Broadcast to all workers
results = os.broadcast_exec(op=OpCode.ADD, a=5, b=3)
# Returns {1: (8,0), 2: (8,0), ..., 8: (8,0)}

Single-Step Execution

# Execute exactly one tick
state = os.step()
# Returns {
#   'tick': 42,
#   'messages_delivered': 1,
#   'nodes': {0: {'status': 'IDLE', ...}, ...}
# }

Bubble Machine

bubble = BubbleMachine(os)
bubble.load([64, 25, 12, 22, 11, 90, 42, 7])

# Run until settled
cycles = bubble.run()

# Or step through
for state in bubble.run_stepping():
    print(f"Cycle {state['cycle']}: {state['values']}")
    if state['sorted']:
        break

Trace and Replay

# Start recording
os.start_recording()

# ... do operations ...
bubble.run()

# Stop and get log
log = os.stop_recording()

# Replay
os.replay(log)  # Produces identical execution

Shell Interface

shell = SquaresShell(os)
shell.run_interactive()
> nodes
● node0  master   IDLE     msgs:8
● node1  worker   IDLE     msgs:1
...

> bubble load 64 25 12 22 11 90 42 7
> bubble run
Settled in 5 cycles

> bubble trace 5
[t= 439] EVEN  pair(n5,n6) 25<=>42 (no swap)
...

Trace Examples

Boot Sequence Trace

[     1] Node 0: SEND     PING #1 → Node 1
[     2] Node 1: RECV     PING #1
[     3] Node 1: SEND     PONG #1 → Node 0
[     3] Node 0: RECV     PONG #1
[     4] Node 0: SEND     PING #2 → Node 2
...

Bubble Machine Trace

[t= 112] EVEN     pair(n1,n2) 64<->25 => (25,64)
[t= 124] EVEN     pair(n3,n4) 12<->22 => (12,22)
[t= 136] EVEN     pair(n5,n6) 11<->90 => (11,90)
[t= 148] EVEN     pair(n7,n8) 42<->7  => (7,42)
[t= 160] ODD      pair(n2,n3) 64<->12 => (12,64)
[t= 172] ODD      pair(n4,n5) 22<->11 => (11,22)
[t= 184] ODD      pair(n6,n7) 90<->42 => (42,90)
...
[t= 475] ODD      pair(n6,n7) 42<=>64 (no swap)

Trace Format

[tick] PHASE    pair(nA,nB) valA<->valB => (newA,newB)  # swap occurred
[tick] PHASE    pair(nA,nB) valA<=>valB (no swap)      # no swap needed

Comparisons

Hollywood Squares vs Unix

Aspect Unix Hollywood Squares
Fundamental unit Process Node + Handler
Communication Files, pipes, signals Messages only
State Global filesystem Node-local memory
Time Wall clock Deterministic ticks
Debugging Core dumps, logs Trace + replay
Manages Resources Meaning

Hollywood Squares vs Erlang

Aspect Erlang Hollywood Squares
Processes Lightweight, many Fixed nodes
Messages Async, unordered Deterministic order
State Process-local Node-local
Nondeterminism Allowed Forbidden
Replay Not built-in First-class
Verification Post-hoc By construction

Hollywood Squares vs Neural Networks

Aspect Neural Networks Hollywood Squares
Computation Matrix multiply Message handlers
Transparency Opaque Fully observable
Determinism Often not Always
Compositionality Limited First-class
Debugging Difficult Single-step
Verification Statistical Exhaustive possible

Hollywood Squares vs Cellular Automata

Aspect Cellular Automata Hollywood Squares
Communication Neighbor state read Explicit messages
Synchronization Global clock Message-driven
Observability State snapshots Full trace
Replay Possible Built-in
Topology Fixed grid Configurable

Historical Context

The Lineage

System Year Primitive
Unix 1970s Processes + files
Erlang 1980s Lightweight processes + messages
Plan 9 1990s Everything is a file
Hollywood Squares 2024 Everything is a message with meaning

What Changed

  • Unix asked: How do we share a computer?
  • Erlang asked: How do we handle failures?
  • Plan 9 asked: How do we unify interfaces?
  • Hollywood Squares asks: How do we make correctness scale?

The Paradigm Shift

From: "Verify correctness post-hoc" To: "Construct correctness by design"

Figures and Diagrams

Figure 1: System Architecture

┌─────────────────────────────────────────┐
│           MASTER (Node 0)               │
│  ┌─────────────────────────────────┐    │
│  │       FABRIC KERNEL             │    │
│  │  Directory│Router│Supervisor    │    │
│  └─────────────────────────────────┘    │
│  ┌─────────────────────────────────┐    │
│  │       NODE KERNEL               │    │
│  │  Mailbox│Dispatcher│Handlers    │    │
│  └─────────────────────────────────┘    │
└───────────────────┬─────────────────────┘
        ┌───────────┼───────────┐
        ▼           ▼           ▼
   ┌─────────┐ ┌─────────┐ ┌─────────┐
   │Worker 1 │ │Worker 2 │ │  ...8   │
   └─────────┘ └─────────┘ └─────────┘

Figure 2: Message Frame

┌────┬────┬────┬────┬────┬────┬──────────────────┐
│Type│ ID │Src │Dst │Len │Flag│     Payload      │
│ 1B │ 1B │ 1B │ 1B │ 1B │ 1B │       10B        │
└────┴────┴────┴────┴────┴────┴──────────────────┘
                    16 bytes total

Figure 3: Bubble Machine Phases (Line)

EVEN Phase:
  [n1]──[n2]  [n3]──[n4]  [n5]──[n6]  [n7]──[n8]
    └──┬──┘     └──┬──┘     └──┬──┘     └──┬──┘
     compare    compare    compare    compare

ODD Phase:
  [n1]  [n2]──[n3]  [n4]──[n5]  [n6]──[n7]  [n8]
          └──┬──┘     └──┬──┘     └──┬──┘
           compare    compare    compare

Figure 4: Convergence Visualization

Cycle 0: [64][25][12][22][11][90][42][ 7]  ← Unsorted
            ↓
Cycle 1: [25][12][64][11][22][ 7][90][42]  ← 5 swaps
            ↓
Cycle 2: [12][11][25][ 7][64][22][42][90]  ← 6 swaps
            ↓
Cycle 3: [11][ 7][12][22][25][42][64][90]  ← 6 swaps
            ↓
Cycle 4: [ 7][11][12][22][25][42][64][90]  ← 1 swap
            ↓
Cycle 5: [ 7][11][12][22][25][42][64][90]  ← 0 swaps (SETTLED)

Figure 5: Three-Layer Architecture

┌─────────────────────────────────────────┐
│         COGNITIVE LAYER                 │
│   Fields, Waves, Relaxation, Learning   │
├─────────────────────────────────────────┤
│         KERNEL CONTRACT                 │
│   Mailbox, Dispatcher, Handlers, Replay │
├─────────────────────────────────────────┤
│      COMPUTATIONAL SUBSTRATE            │
│   Nodes, Messages, Ticks, Memory        │
└─────────────────────────────────────────┘

Key Sentences

For Different Audiences

Systems reviewers:

"A distributed microkernel with message-passing syscalls and deterministic replay for addressable processor networks."

ML reviewers:

"Learning as manufacturing: trained computation becomes versioned, verified, deployable artifacts composable into distributed systems."

Distributed systems reviewers:

"We prove that deterministic message passing + bounded local semantics + enforced observability yields global convergence with inherited correctness."

General audience:

"A machine where you can watch every thought, trace every decision, and replay any moment."

Quotable Lines

  • "Structure is meaning."
  • "The topology IS the algorithm."
  • "The bus IS the computer."
  • "Hollywood Squares manages meaning, not resources."
  • "This is a proof of distributed convergence under strict observability constraints."
  • "We didn't solve distributed correctness—we changed the rules so it propagates naturally."
  • "Debugging becomes observation, not archaeology."

The Identity

"A coordination OS for verified compositional intelligence."

Related Work

Actor Model (Hewitt, 1973)

  • Shared: Message-passing philosophy
  • Different: Hollywood Squares enforces determinism and provides replay

Erlang/OTP (Armstrong, 1980s)

  • Shared: Lightweight processes, supervision trees
  • Different: Erlang allows nondeterminism; we forbid it

Dataflow Architectures

  • Shared: Execution driven by data availability
  • Different: We add explicit phases and full observability

Cellular Automata (Wolfram, 1984)

  • Shared: Local rules → global behavior
  • Different: CA reads neighbor state; we use explicit messages

Sorting Networks (Batcher, 1968)

  • Shared: Parallel compare-swap
  • Different: We execute via message passing with full trace

Distributed Snapshots (Chandy-Lamport, 1985)

  • Shared: Capturing global state
  • Different: We capture complete trace, not just consistent cuts

Plan 9 (Pike et al., 1990)

  • Shared: Unifying abstraction
  • Different: Plan 9 = files; Hollywood Squares = messages with meaning

The Constraint Field (NEW)

The Second Demo

While the Bubble Machine proves distributed convergence, the Constraint Field proves semantic emergence under constraint.

"This system doesn't search for solutions. It relaxes toward them."

Architecture

┌─────────────────────────────────────────┐
│           CONSTRAINT FIELD              │
│  ┌─────┬─────┬─────┬─────┬─────┐       │
│  │cell │cell │cell │cell │cell │  ...  │
│  │ 1   │ 2   │ 3   │ 4   │ 5   │       │
│  └──┬──┴──┬──┴──┬──┴──┬──┴──┬──┘       │
│     │     │     │     │                 │
│  ┌──┴─────┴─────┴─────┴──┐             │
│  │    ALL-DIFFERENT       │             │
│  │    CONSTRAINT          │             │
│  └───────────────────────┘             │
└─────────────────────────────────────────┘

Handlers

Handler Input Output Semantics
DOMAIN_GET — (lo, hi) Return domain bitmask
DOMAIN_SET lo, hi (lo, hi) Set domain
DOMAIN_DELTA mask_lo, mask_hi (changed, entropy) Remove values from domain
IS_SINGLETON — (is_single, count) Check if resolved
GET_VALUE — (value, entropy) Get singleton value

The Money Shot

============================================================
PUZZLE: What must cell 8 be?
============================================================

8 cells, all must be different, values 1-8 only.

Given: cells 1-7 are {1,2,3,4,5,6,7}
Question: What is cell 8?

Initial state:
n8 (2,1): {1,2,3,4,5,6,7,8}    entropy=8

============================================================
PROPAGATION
============================================================

--- Tick 1 ---
n8 (2,1): [8]                  FIXED

  >>> CELL 8 RESOLVED: 8

*** SOLVED! ***

============================================================
WHY is cell 8 = 8?
============================================================

Cell (2,1) - node 8
Current domain: [8]

History:
  [t=157] removed {1} via cell(0,0)=1
  [t=187] removed {2} via cell(0,1)=2
  [t=217] removed {3} via cell(0,2)=3
  [t=247] removed {4} via cell(1,0)=4
  [t=277] removed {5} via cell(1,1)=5
  [t=307] removed {6} via cell(1,2)=6
  [t=337] removed {7} via cell(2,0)=7

The answer was FORCED by the constraints.
No search. No guessing. Just propagation.

Why This Matters

  1. Explainable — Every elimination has a reason
  2. Traceable — Complete history of every cell
  3. Replayable — Identical execution from trace
  4. No Search — Pure propagation, no backtracking

The Sentence

"You can watch a problem think."

Future Work

Immediate (v0.2)

  1. Constraint Machine — Arc consistency and unit propagation as message-passing relaxation
  2. Canonicalize Bubble Machine — Reference documentation, diagrams, tutorial

Near-term

  1. Network Silicon — Packet classification micro-engines for routers/switches
  2. Learned Handlers — Train → freeze → verify → deploy pipeline
  3. Hierarchical Topologies — Trees of grids, recursive coordination

Long-term

  1. Formal Verification — Machine-checked proofs of handler correctness
  2. Hardware Implementation — FPGA/ASIC realization
  3. Language Support — DSL for topology and handler specification

Appendices

A: Complete Message Type Table

Code Name Direction Payload Response
0x00 NOP — — —
0x01 PING Request — PONG
0x02 PONG Response status, load —
0x03 EXEC Request op, a, b, flags EXEC_OK/ERR
0x04 EXEC_OK Response result, extra —
0x05 EXEC_ERR Response error_code —
0x06 LOAD Request program_id LOAD_OK
0x07 LOAD_OK Response — —
0x08 DUMP Request addr, len DUMP_DATA
0x09 DUMP_DATA Response data —
0x0A RESET Command — —
0x0B TRACE Event event_data —
0x0C ROUTE Request work_data EXEC_OK
0x0D STATUS Request — STATUS_RPL
0x0E STATUS_RPL Response status_data —
0x0F HALT Command — —
0x20 GET Request — (value, 0)
0x21 SET Request value (value, 0)
0x22 CSWAP Request neighbor_val, dir (my_val, swapped)

B: Shell Command Reference

Basic Operations:
  nodes               List all nodes
  ping <n>            Health check node n
  send <n> <a> <b>    Execute ADD on node n
  run <n|all> <op> <a> <b>  Execute operation
  route <op> <a> <b>  Route to best node
  topo                Show topology
  stats               System statistics
  inspect <n>         Inspect node state

Single-Step:
  step [n]            Execute n ticks
  pause               Pause execution
  resume              Resume execution
  snapshot            Capture state
  record [start|stop|show]  Recording control
  replay              Replay recorded session

Bubble Machine:
  bubble load <v1> <v2> ...  Load values
  bubble random [seed]       Random values
  bubble run                 Run until settled
  bubble step                One cycle
  bubble phase               One phase
  bubble show                Show field
  bubble trace [n]           Show last n events
  bubble phases              Show phase schedule
  bubble topo <type>         Set topology (line|ring|grid)

C: Implementation Statistics

Component Lines of Code
message.py 252
node_kernel.py 432
fabric_kernel.py 342
system.py 649
shell.py 685
bubble_machine.py 487
sorting_fabric.py 318
sorting_network.py 393
Total ~3,600

D: Reproducibility Checklist

  • Python 3.10+ installed
  • No external dependencies required
  • Run: python experiments/run_bubble_machine.py
  • Verify: Cycles ≤ 5, Swaps = 18, Sorted = True
  • Compare trace format to paper

Contact

[To be filled in before submission]

The field relaxes. Structure is meaning.

December 14, 2024