Dontopedia

Dense commutator table

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

Dense commutator table has 22 facts recorded in Dontopedia across 6 references, with 2 live disagreements.

22 facts·18 predicates·6 sources·2 in dispute

Mostly:used by(2), rdf:type(2), eliminates(2)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (9)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

usesUses(2)

builtDenseCommutatorTableBuilt Dense Commutator Table(1)

computesComputes(1)

crushingCrushing(1)

dependsOnDepends on(1)

listsReasonOneLists Reason One(1)

usesSameUses Same(1)

usesSameTableAsUses Same Table As(1)

Other facts (21)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

21 facts
PredicateValueRef
Used byGpu Kernel[2]
Used byGpu Kernel[5]
Rdf:typeOptimization Technique[4]
Rdf:typeData Structure[6]
EliminatesPointer Chasing[4]
EliminatesBranch Misprediction[4]
Enables Auto VectorizationInner for Loop K0to6[1]
Delivers SpeedupOverall Speedup[1]
Has Size Bytes864[1]
Resides in L1 CacheL1 Cache[1]
Eliminates Branch MispredictionsBranch Mispredictions[1]
Eliminates Pointer ChasingPointer Chasing[1]
Presupposes Commutator UsageClifford Algebra[1]
Achieves Performance10M → 2.4B pts/s[3]
High Performance Gain10M to 2.4B pts/s[3]
Uses Metal GpuMetal Gpu[3]
Uses RayonRayon[3]
Memory Footprint864[4]
Memory Unitbytes[4]
Resides in CacheL1 Cache[4]
EnablesAuto Vectorization[4]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

enablesAutoVectorizationblah/watt-activation/part-527
ex:inner-for-loop-k0to6
deliversSpeedupblah/watt-activation/part-527
ex:overall-speedup
hasSizeBytesblah/watt-activation/part-527
864
residesInL1Cacheblah/watt-activation/part-527
ex:l1-cache
eliminatesBranchMispredictionsblah/watt-activation/part-527
ex:branch-mispredictions
eliminatesPointerChasingblah/watt-activation/part-527
ex:pointer-chasing
presupposesCommutatorUsageblah/watt-activation/part-527
ex:clifford-algebra
usedByblah/watt-activation/part-535
ex:gpu-kernel
achievesPerformanceblah/watt-activation/part-549
10M → 2.4B pts/s
highPerformanceGainblah/watt-activation/part-549
10M to 2.4B pts/s
usesMetalGpublah/watt-activation/part-549
ex:metal-gpu
usesRayonblah/watt-activation/part-549
ex:rayon
typeblah/watt-activation/524
ex:OptimizationTechnique
labelblah/watt-activation/524
Dense commutator table
memoryFootprintblah/watt-activation/524
864
memoryUnitblah/watt-activation/524
bytes
residesInCacheblah/watt-activation/524
ex:L1-cache
eliminatesblah/watt-activation/524
ex:pointer-chasing
eliminatesblah/watt-activation/524
ex:branch-misprediction
enablesblah/watt-activation/524
ex:auto-vectorization
usedByblah/watt-activation/532
ex:gpu-kernel
typeblah/watt-activation/547
ex:DataStructure

References (6)

6 references
  1. [1]Part 5277 facts
    ctx:discord/blah/watt-activation/part-527
  2. [2]Part 5351 fact
    ctx:discord/blah/watt-activation/part-535
  3. [3]Part 5494 facts
    ctx:discord/blah/watt-activation/part-549
  4. [4]5248 facts
    ctx:discord/blah/watt-activation/524
    • full textwatt-activation-524
      text/plain3 KBdoc:agent/watt-activation-524/7be280bc-6f35-4f26-ab03-e8a9220e30ed
      Show excerpt
      [2026-03-23 01:54] xenonfun: Performance Results ``` ┌───────────┬───────────────┬───────────────┬─────────┐ │ Grid size │ Before │ After │ Speedup │ ├───────────┼───────────────┼───────────────┼─────────┤ │ n=512
  5. [5]5321 fact
    ctx:discord/blah/watt-activation/532
    • full textwatt-activation-532
      text/plain3 KBdoc:agent/watt-activation-532/10d55f18-88f7-405c-9c2c-bd69daaefb6d
      Show excerpt
      [2026-03-23 03:17] xenonfun: - Orchestrator (resonate-server) that manages the global field, assigns slices, verifies results - Worker client (resonate-client) that auto-generates Nostr identity, benchmarks hardware, computes slices,
  6. [6]5471 fact
    ctx:discord/blah/watt-activation/547
    • full textwatt-activation-547
      text/plain2 KBdoc:agent/watt-activation-547/5df4b8d4-896d-4a30-bbd9-886176abaf0c
      Show excerpt
      [2026-03-23 06:10] xenonfun: ⏺ Yes — the current design handles that naturally: Joining: A worker registers at any time via POST /api/resonate/register, gets an immediate assignment if there's work available, and starts computing. Mid-

See also

Keep researching

Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.