v3 performance optimization

仓库: ruvnet/claude-flow
安装量: 42
排名: #17198

安装

npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill 'V3 Performance Optimization'

V3 Performance Optimization What This Skill Does Validates and optimizes claude-flow v3 to achieve industry-leading performance through Flash Attention, AgentDB HNSW indexing, and comprehensive system optimization with continuous benchmarking. Quick Start

Initialize performance optimization

Task ( "Performance baseline" , "Establish v2 performance benchmarks" , "v3-performance-engineer" )

Target validation (parallel)

Task
(
"Flash Attention"
,
"Validate 2.49x-7.47x speedup target"
,
"v3-performance-engineer"
)
Task
(
"Search optimization"
,
"Validate 150x-12,500x search improvement"
,
"v3-performance-engineer"
)
Task
(
"Memory optimization"
,
"Achieve 50-75% memory reduction"
,
"v3-performance-engineer"
)
Performance Target Matrix
Flash Attention Revolution
┌─────────────────────────────────────────┐
│ FLASH ATTENTION │
├─────────────────────────────────────────┤
│ Baseline: Standard attention │
│ Target: 2.49x - 7.47x speedup │
│ Memory: 50-75% reduction │
│ Latency: Sub-millisecond processing │
└─────────────────────────────────────────┘
Search Performance Revolution
┌─────────────────────────────────────────┐
│ SEARCH OPTIMIZATION │
├─────────────────────────────────────────┤
│ Current: O(n) linear search │
│ Target: 150x - 12,500x improvement │
│ Method: HNSW indexing │
│ Latency: <100ms for 1M+ entries │
└─────────────────────────────────────────┘
Comprehensive Benchmark Suite
Startup Performance
class
StartupBenchmarks
{
async
benchmarkColdStart
(
)
:
Promise
<
BenchmarkResult
>
{
const
startTime
=
performance
.
now
(
)
;
await
this
.
initializeCLI
(
)
;
await
this
.
initializeMCPServer
(
)
;
await
this
.
spawnTestAgent
(
)
;
const
totalTime
=
performance
.
now
(
)
-
startTime
;
return
{
total
:
totalTime
,
target
:
500
,
// ms
achieved
:
totalTime
<
500
}
;
}
}
Memory Operation Benchmarks
class
MemoryBenchmarks
{
async
benchmarkVectorSearch
(
)
:
Promise
<
SearchBenchmark
>
{
const
queries
=
this
.
generateTestQueries
(
10000
)
;
// Baseline: Current linear search
const
baselineTime
=
await
this
.
timeOperation
(
(
)
=>
this
.
currentMemory
.
searchAll
(
queries
)
)
;
// Target: HNSW search
const
hnswTime
=
await
this
.
timeOperation
(
(
)
=>
this
.
agentDBMemory
.
hnswSearchAll
(
queries
)
)
;
const
improvement
=
baselineTime
/
hnswTime
;
return
{
baseline
:
baselineTime
,
hnsw
:
hnswTime
,
improvement
,
targetRange
:
[
150
,
12500
]
,
achieved
:
improvement
>=
150
}
;
}
async
benchmarkMemoryUsage
(
)
:
Promise
<
MemoryBenchmark
>
{
const
baseline
=
process
.
memoryUsage
(
)
.
heapUsed
;
await
this
.
loadTestDataset
(
)
;
const
withData
=
process
.
memoryUsage
(
)
.
heapUsed
;
await
this
.
enableOptimization
(
)
;
const
optimized
=
process
.
memoryUsage
(
)
.
heapUsed
;
const
reduction
=
(
withData
-
optimized
)
/
withData
;
return
{
baseline
,
withData
,
optimized
,
reductionPercent
:
reduction
*
100
,
targetReduction
:
[
50
,
75
]
,
achieved
:
reduction
>=
0.5
}
;
}
}
Swarm Coordination Benchmarks
class
SwarmBenchmarks
{
async
benchmark15AgentCoordination
(
)
:
Promise
<
SwarmBenchmark
>
{
const
agents
=
await
this
.
spawn15Agents
(
)
;
// Coordination latency
const
coordinationTime
=
await
this
.
timeOperation
(
(
)
=>
this
.
coordinateSwarmTask
(
agents
)
)
;
// Task decomposition
const
decompositionTime
=
await
this
.
timeOperation
(
(
)
=>
this
.
decomposeComplexTask
(
)
)
;
// Consensus achievement
const
consensusTime
=
await
this
.
timeOperation
(
(
)
=>
this
.
achieveSwarmConsensus
(
agents
)
)
;
return
{
coordination
:
coordinationTime
,
decomposition
:
decompositionTime
,
consensus
:
consensusTime
,
agentCount
:
15
,
efficiency
:
this
.
calculateEfficiency
(
agents
)
}
;
}
}
Flash Attention Benchmarks
class
AttentionBenchmarks
{
async
benchmarkFlashAttention
(
)
:
Promise
<
AttentionBenchmark
>
{
const
sequences
=
this
.
generateSequences
(
[
512
,
1024
,
2048
,
4096
]
)
;
const
results
=
[
]
;
for
(
const
sequence
of
sequences
)
{
// Baseline attention
const
baselineResult
=
await
this
.
benchmarkStandardAttention
(
sequence
)
;
// Flash attention
const
flashResult
=
await
this
.
benchmarkFlashAttention
(
sequence
)
;
results
.
push
(
{
sequenceLength
:
sequence
.
length
,
speedup
:
baselineResult
.
time
/
flashResult
.
time
,
memoryReduction
:
(
baselineResult
.
memory
-
flashResult
.
memory
)
/
baselineResult
.
memory
,
targetSpeedup
:
[
2.49
,
7.47
]
,
achieved
:
this
.
checkTarget
(
flashResult
,
[
2.49
,
7.47
]
)
}
)
;
}
return
{
results
,
averageSpeedup
:
this
.
calculateAverage
(
results
,
'speedup'
)
,
averageMemoryReduction
:
this
.
calculateAverage
(
results
,
'memoryReduction'
)
}
;
}
}
SONA Learning Benchmarks
class
SONABenchmarks
{
async
benchmarkAdaptationTime
(
)
:
Promise
<
SONABenchmark
>
{
const
scenarios
=
[
'pattern_recognition'
,
'task_optimization'
,
'error_correction'
,
'performance_tuning'
]
;
const
results
=
[
]
;
for
(
const
scenario
of
scenarios
)
{
const
startTime
=
performance
.
hrtime
.
bigint
(
)
;
await
this
.
sona
.
adapt
(
scenario
)
;
const
endTime
=
performance
.
hrtime
.
bigint
(
)
;
const
adaptationTimeMs
=
Number
(
endTime
-
startTime
)
/
1000000
;
results
.
push
(
{
scenario
,
adaptationTime
:
adaptationTimeMs
,
target
:
0.05
,
// ms
achieved
:
adaptationTimeMs
<=
0.05
}
)
;
}
return
{
scenarios
:
results
,
averageTime
:
results
.
reduce
(
(
sum
,
r
)
=>
sum
+
r
.
adaptationTime
,
0
)
/
results
.
length
,
successRate
:
results
.
filter
(
r
=>
r
.
achieved
)
.
length
/
results
.
length
}
;
}
}
Performance Monitoring Dashboard
Real-time Metrics
class
PerformanceMonitor
{
async
collectMetrics
(
)
:
Promise
<
PerformanceSnapshot
>
{
return
{
timestamp
:
Date
.
now
(
)
,
flashAttention
:
await
this
.
measureFlashAttention
(
)
,
searchPerformance
:
await
this
.
measureSearchSpeed
(
)
,
memoryUsage
:
await
this
.
measureMemoryEfficiency
(
)
,
startupTime
:
await
this
.
measureStartupLatency
(
)
,
sonaAdaptation
:
await
this
.
measureSONASpeed
(
)
,
swarmCoordination
:
await
this
.
measureSwarmEfficiency
(
)
}
;
}
async
generateReport
(
)
:
Promise
<
PerformanceReport
>
{
const
snapshot
=
await
this
.
collectMetrics
(
)
;
return
{
summary
:
this
.
generateSummary
(
snapshot
)
,
achievements
:
this
.
checkTargetAchievements
(
snapshot
)
,
trends
:
this
.
analyzeTrends
(
)
,
recommendations
:
this
.
generateOptimizations
(
)
,
regressions
:
await
this
.
detectRegressions
(
)
}
;
}
}
Continuous Regression Detection
class
PerformanceRegression
{
async
detectRegressions
(
)
:
Promise
<
RegressionReport
>
{
const
current
=
await
this
.
runFullBenchmark
(
)
;
const
baseline
=
await
this
.
getBaseline
(
)
;
const
regressions
=
[
]
;
for
(
const
[
metric
,
currentValue
]
of
Object
.
entries
(
current
)
)
{
const
baselineValue
=
baseline
[
metric
]
;
const
change
=
(
currentValue
-
baselineValue
)
/
baselineValue
;
if
(
change
<
-
0.05
)
{
// 5% regression threshold
regressions
.
push
(
{
metric
,
baseline
:
baselineValue
,
current
:
currentValue
,
regressionPercent
:
change
*
100
,
severity
:
this
.
classifyRegression
(
change
)
}
)
;
}
}
return
{
hasRegressions
:
regressions
.
length
>
0
,
regressions
,
recommendations
:
this
.
generateRegressionFixes
(
regressions
)
}
;
}
}
Optimization Strategies
Memory Optimization
class
MemoryOptimization
{
async
optimizeMemoryUsage
(
)
:
Promise
<
OptimizationResult
>
{
// Implement memory pooling
await
this
.
setupMemoryPools
(
)
;
// Enable garbage collection tuning
await
this
.
optimizeGarbageCollection
(
)
;
// Implement object reuse patterns
await
this
.
setupObjectPools
(
)
;
// Enable memory compression
await
this
.
enableMemoryCompression
(
)
;
return
this
.
validateMemoryReduction
(
)
;
}
}
CPU Optimization
class
CPUOptimization
{
async
optimizeCPUUsage
(
)
:
Promise
<
OptimizationResult
>
{
// Implement worker thread pools
await
this
.
setupWorkerThreads
(
)
;
// Enable CPU-specific optimizations
await
this
.
enableSIMDInstructions
(
)
;
// Implement task batching
await
this
.
optimizeTaskBatching
(
)
;
return
this
.
validateCPUImprovement
(
)
;
}
}
Target Validation Framework
Performance Gates
class
PerformanceGates
{
async
validateAllTargets
(
)
:
Promise
<
ValidationReport
>
{
const
results
=
await
Promise
.
all
(
[
this
.
validateFlashAttention
(
)
,
// 2.49x-7.47x
this
.
validateSearchPerformance
(
)
,
// 150x-12,500x
this
.
validateMemoryReduction
(
)
,
// 50-75%
this
.
validateStartupTime
(
)
,
// <500ms
this
.
validateSONAAdaptation
(
)
// <0.05ms
]
)
;
return
{
allTargetsAchieved
:
results
.
every
(
r
=>
r
.
achieved
)
,
results
,
overallScore
:
this
.
calculateOverallScore
(
results
)
,
recommendations
:
this
.
generateRecommendations
(
results
)
}
;
}
}
Success Metrics
Primary Targets
Flash Attention
2.49x-7.47x speedup validated
Search Performance
150x-12,500x improvement confirmed
Memory Reduction
50-75% usage optimization achieved
Startup Time
<500ms cold start consistently
SONA Adaptation
<0.05ms learning response time
15-Agent Coordination
Efficient parallel execution
Continuous Monitoring
Performance Dashboard
Real-time metrics collection
Regression Testing
Automated performance validation
Trend Analysis
Performance evolution tracking
Alert System
Immediate regression notification Related V3 Skills v3-integration-deep - Performance integration with agentic-flow v3-memory-unification - Memory performance optimization v3-swarm-coordination - Swarm performance coordination v3-security-overhaul - Secure performance patterns Usage Examples Complete Performance Validation

Full performance suite

npm run benchmark:v3

Specific target validation

npm run benchmark:flash-attention npm run benchmark:agentdb-search npm run benchmark:memory-optimization

Continuous monitoring

npm run monitor:performance

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