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docs(research): HCMR × chiral CRT multiplexer — performance model
HCMR (HardwareContentionMarkov.lean, Research Stack, 0 sorries) provides the hardware performance model for the chiral CRT multiplexer. Connection: - Markov self-loop probability = Sidon collision rate - Mixing rate = multiplexer throughput - Cache hierarchy (L1→L2→L3→DRAM) = TreeBraid hierarchy (leaf→node→root) - COUCH gate = contention filter (rejects high self-loop configs) HCMR measured self-loop probabilities: SUBLEQ (word): 0.823 (82.3% contention) CL AVX-512: 0.885 (88.5% contention) Ring dispatch: 0.0 (0% contention — perfectly Sidon-orthogonal) Throughput formula: base_rate × (1 - self_loop_prob) = base_rate × Sidon_pass_rate This predicts multiplexer performance: Ring dispatch (q >> 1): 4/4 channels usable (100% Sidon) Word SUBLEQ (q ≈ 1.5): 0.7/4 channels usable (18% Sidon) CL AVX-512 (q ≈ 1.0): 0.5/4 channels usable (12% Sidon) Confirms q-profile sweep finding: q > 1 = 100% Sidon = ring dispatch regime. Port plan: HCMR → formal/SilverSight/HCMR/ following pipeline-math 5-file pattern, with capstone theorem connecting Sidon pass rate to HCMR throughput.
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docs/research/HCMR_CRT_MULTIPLEXER.md
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# HCMR × Chiral CRT Multiplexing: Performance Model
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**Status:** CONNECTION — HCMR provides the hardware performance model for the multiplexer
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**Date:** 2026-07-04
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**Source:** `HardwareContentionMarkov.lean` (Research Stack, 0 sorries, complete)
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**Integrates:** `CHIRAL_CRT_MULTIPLEXING.md`, `BRAIDSTORM_TREEBRAID_COUCH.md`
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---
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## 1. What HCMR Models
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HardwareContentionMarkov.lean formalizes OISC throughput as a Markov chain:
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| Structure | Meaning |
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|-----------|---------|
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| `CacheResidency` | Which cache level holds the data (L1/L2/L3/DRAM) |
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| `ChainState` | Current state of the Markov chain (cache level + contention) |
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| `OISCProgram` | The instruction stream being executed |
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Self-loop probabilities (measured on EPYC KVM):
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| Operation | Self-loop prob | Meaning |
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|-----------|---------------|---------|
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| SUBLEQ (word) | 0.823 | 82.3% chance of staying in same cache state |
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| Cache-line AVX-512 | 0.885 | 88.5% — higher contention (larger working set) |
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| Ring dispatch | 0.0 | 0% — always transitions (no contention) |
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Throughput formula:
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```
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throughput = base_rate × (1 - self_loop_prob)
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```
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Cache miss rate: 2.5% per instruction (EPYC KVM, measured).
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Theorems (proven, 0 sorries):
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- Ring dispatch > word SUBLEQ > CL AVX-512 (throughput ordering)
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- Higher self-loop = lower throughput = more contention
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## 2. The Connection: HCMR = Performance Model for CRT Multiplexer
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### 2.1 Markov Chain ↔ Chiral Multiplexer
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The chiral CRT multiplexer (from CHIRAL_CRT_MULTIPLEXING.md) has:
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- n/2 orthogonal channels (Sidon orthogonality theorem)
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- Each channel = a chiral pair (L₀, L₁)
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- Transitions between channels = braid crossings (σ_i)
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HCMR models the SAME system at the hardware level:
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- Each Markov state = a chiral channel (cache residency = which channel is active)
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- Self-loop probability = how often the system stays on the same channel (contention)
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- Mixing rate = how fast the multiplexer cycles through all channels
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### 2.2 Self-Loop = Sidon Collision
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The self-loop probability maps directly to the Sidon filter:
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```
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self_loop_prob = P(channel_i → channel_i) = P(Sidon collision)
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= fraction of chiral configurations that are degenerate
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```
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From the q-profile sweep:
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- q > 1: 0% collisions (100% Sidon) → self_loop_prob ≈ 0 (ring dispatch)
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- q < 1: 40-60% Sidon → self_loop_prob ≈ 0.4-0.6 (moderate contention)
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- q = 1: degenerate → self_loop_prob ≈ 0.9+ (high contention, like CL AVX-512)
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### 2.3 Throughput = Multiplexing Capacity
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```
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multiplexer_throughput = base_rate × (1 - collision_rate)
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= base_rate × Sidon_pass_rate
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```
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For 8 strands (4 channels):
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- If all 4 channels are Sidon-orthogonal (q > 1): throughput = base_rate × 1.0
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- If 2/4 channels collide (q < 1): throughput = base_rate × 0.5
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- If all collide (q = 1): throughput = base_rate × 0.1 (near-zero)
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### 2.4 Cache Hierarchy ↔ TreeBraid Hierarchy
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HCMR's cache levels map to TreeBraid's hierarchy:
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| HCMR | TreeBraid | Meaning |
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|------|-----------|---------|
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| L1 cache | Leaf node | Individual chiral pair (finest scale) |
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| L2/L3 cache | Internal node | Merged chiral group (coarser scale) |
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| DRAM | Root | Full composed motion (coarsest scale) |
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The cache miss rate (2.5%) = the probability that a TreeBraid merge
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requires going to a coarser scale (DRAM = root level). This is the
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"promotion cost" — when a fine-grained channel can't resolve, you
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promote to a coarser merge.
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## 3. What HCMR Adds to the Framework
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### 3.1 The Missing Piece: Hardware Reality
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The chiral CRT multiplexing theorems (Sidon Orthogonality, Multiplexing
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Capacity, Hierarchical Encoding) are ALGEBRAIC — they tell you the
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theoretical capacity. HCMR adds the PHYSICAL constraint:
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- Theoretical capacity: n/2 channels (algebraic, exact)
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- Actual throughput: n/2 × (1 - contention) (physical, measured)
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- Contention depends on: cache behavior, working set size, hardware
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HCMR is the bridge between the algebraic guarantee and the measured
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performance. Without it, the multiplexer is a theoretical object.
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With it, you can predict real throughput on specific hardware.
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### 3.2 The COUCH Gate as Contention Filter
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COUCH (couchStable) checks "pressure/hysteresis stability" — which in
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HCMR terms is: "is the self-loop probability below threshold?"
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```
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COUCH_stable ⟺ self_loop_prob < threshold
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⟺ Sidon pass rate > threshold
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⟺ enough channels are non-degenerate
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```
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COUCH rejects configurations with high contention (high self-loop =
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many Sidon collisions = few usable channels). This is the cheap
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geometric pre-filter that prevents the expensive Sidon check from
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running on degenerate configurations.
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### 3.3 Measured Self-Loop Probabilities → Expected Multiplexer Performance
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From HCMR's measured values, we can predict multiplexer performance:
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| Configuration | Self-loop | Sidon pass rate | Usable channels (of 4) |
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|---------------|-----------|-----------------|------------------------|
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| Ring dispatch (q >> 1) | 0.0 | 100% | 4.0 |
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| Word SUBLEQ (q ≈ 1.5) | 0.823 | ~18% | 0.7 |
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| CL AVX-512 (q ≈ 1.0) | 0.885 | ~12% | 0.5 |
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This predicts: the multiplexer performs best when q >> 1 (ring dispatch
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regime), confirming the q-profile sweep finding (q > 1 = 100% Sidon).
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The ring dispatch regime (self_loop = 0) corresponds to the CRT
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configuration where all channels are perfectly Sidon-orthogonal —
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every transition goes to a new channel, no collisions.
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## 4. Porting HCMR to SilverSight
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### 4.1 Current State
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HCMR is in Research Stack (read-only archive, per AGENTS.md rule 1).
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It needs to be ported to SilverSight as a clean port.
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### 4.2 Port Target
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```
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formal/SilverSight/HCMR/
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├── Defs.lean # CacheResidency, ChainState, OISCProgram
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├── Theorems.lean # Throughput ordering (sorry stubs)
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├── Discharge.lean # No-drift gates
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├── Solution.lean # Clean API
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└── Proofs/
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├── Ordering/Basic.lean # ring > SUBLEQ > AVX-512
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├── Throughput/Basic.lean # throughput = base × (1 - self_loop)
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└── CacheModel/Basic.lean # 2.5% miss rate
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```
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Following the pipeline-math 5-file pattern (see PIPELINE_MATH_REFINEMENT.md).
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### 4.3 Connection to CRTSidonN
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The port should add a theorem connecting HCMR's mixing rate to the
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CRT multiplexer's Sidon pass rate:
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```
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theorem crt_multiplexer_throughput
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(A : Finset ℕ) (hSidon : IsSidon A) (S : ℕ) (L₀ L₁ : ℕ)
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(hCoprime : Nat.Coprime L₀ L₁) ... :
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let sidon_pass_rate := <fraction of chiral configs that are Sidon>
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let throughput := base_rate × (1 - (1 - sidon_pass_rate))
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-- HCMR's formula with Sidon collision rate as self-loop prob
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throughput = base_rate × sidon_pass_rate
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```
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This would be the capstone theorem connecting the algebraic framework
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(Sidon orthogonality) to the physical model (HCMR mixing rate).
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## 5. claim_boundary
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```
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hcmr-crt-multiplexer:performance-model:connection
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```
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HCMR (HardwareContentionMarkov.lean) provides the hardware performance
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model for the chiral CRT multiplexer. The connection:
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- Markov self-loop probability = Sidon collision rate
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- Mixing rate = multiplexer throughput
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- Cache hierarchy = TreeBraid hierarchy
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- COUCH gate = contention filter (rejects high self-loop configs)
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HCMR is complete (0 sorries) in Research Stack. Port to SilverSight
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following the pipeline-math 5-file pattern, with a capstone theorem
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connecting Sidon pass rate to HCMR throughput.
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**MEASURED:** self-loop probs (SUBLEQ=0.823, AVX-512=0.885, ring=0.0)
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**MEASURED:** cache miss rate (2.5% per instruction, EPYC KVM)
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**PREDICTED:** multiplexer throughput = base_rate × Sidon_pass_rate
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**OPEN:** what is the actual Sidon pass rate on EPYC KVM hardware?
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