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QuafadasQuafadas
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some benchmarks
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‎benchmark_vs_breeze/src/breezey.scala‎

Lines changed: 3 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -11,18 +11,11 @@ import breeze.numerics.step
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val dataA = DenseMatrix.rand[Double](dim, dim)
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val dataB = DenseMatrix.rand[Double](dim, dim)
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val vectorData = DenseVector.rand[Double](dim)
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println("Breeze Data:")
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println(dataA)
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println(dataB)
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println(vectorData)
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// Representative linear algebra workload
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// Random linear algebra workload
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val step1 = dataA + dataB // Element-wise addition
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val step2 = step1 *:* dataA // Hadamard product
24-
println("Step 2 (Hadamard product):")
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println(step2)
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val step3 = step2 * vectorData // Matrix-vector multiply
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val step4 = step3.map(_ * 2.0 + 1.0) // Element-wise transform
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val step5 = breeze.linalg.norm(step4) // L2 norm
@@ -40,16 +33,11 @@ import breeze.numerics.step
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val matB = vecxt.matrix.Matrix(dataB.toArray, (dim, dim))
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val vec = vectorData.toArray
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43-
println(matA.printMat)
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println(matB.printMat)
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println(vec.mkString("Array(", ", ", ")"))
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// Same representative linear algebra workload
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val step1Vecxt = matA + matB // Element-wise addition
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val step2Vecxt = step1Vecxt.hadamard(matA) // Hadamard product
51-
println("Step 2 (Hadamard product):")
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println(step2Vecxt.printMat)
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val step3Vecxt = step2Vecxt * vec // Matrix-vector multiply
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val step4Vecxt = step3Vecxt.fma(2.0, 1.0) // Element-wise transform
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val step5Vecxt = vecxt.all.norm(step4Vecxt) // L2 norm

‎benchmark_vs_breeze/src/doSomeStuff.scala‎

Lines changed: 22 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -22,26 +22,37 @@ class LinearAlgebraWorkloadBenchmark extends BLASBenchmark:
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var dataB: Array[Double] = uninitialized
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var vectorData: Array[Double] = uninitialized
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@Setup(Level.Invocation)
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// Pre-created matrices for pure computation benchmarking
26+
var breezeMatA: DenseMatrix[Double] = uninitialized
27+
var breezeMatB: DenseMatrix[Double] = uninitialized
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var breezeVec: DenseVector[Double] = uninitialized
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30+
var vecxtMatA: vecxt.matrix.Matrix[Double] = uninitialized
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var vecxtMatB: vecxt.matrix.Matrix[Double] = uninitialized
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@Setup(Level.Trial) // Only once per iteration
2634
def setup(): Unit =
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val dim = matDim.toInt
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dataA = randomDoubleArray(dim * dim)
2937
dataB = randomDoubleArray(dim * dim)
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vectorData = randomDoubleArray(dim)
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// Pre-create matrices to exclude construction overhead
41+
breezeMatA = new DenseMatrix(dim, dim, dataA.clone())
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breezeMatB = new DenseMatrix(dim, dim, dataB.clone())
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breezeVec = new DenseVector(vectorData.clone())
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vecxtMatA = vecxt.matrix.Matrix(dataA.clone(), (dim, dim))
46+
vecxtMatB = vecxt.matrix.Matrix(dataB.clone(), (dim, dim))
3147
end setup
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3349
@Benchmark
3450
def breezeWorkload(bh: Blackhole): Unit =
35-
val dim = matDim.toInt
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// Create matrices and vector from the same data
37-
val matA = new DenseMatrix(dim, dim, dataA)
38-
val matB = new DenseMatrix(dim, dim, dataB)
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val vec = new DenseVector(vectorData)
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// Representative linear algebra workload
42-
val step1 = matA + matB // Element-wise addition
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val step2 = step1 *:* matA // Hadamard product
44-
val step3 = step2 * vec // Matrix-vector multiply
53+
val step1 = breezeMatA + breezeMatB // Element-wise addition
54+
val step2 = step1 *:* breezeMatA // Hadamard product
55+
val step3 = step2 * breezeVec // Matrix-vector multiply
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val step4 = step3.map(_ * 2.0 + 1.0) // Element-wise transform
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val step5 = breeze.linalg.norm(step4) // L2 norm
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// val step6 = step2.t // Transpose
@@ -55,14 +66,10 @@ class LinearAlgebraWorkloadBenchmark extends BLASBenchmark:
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@Benchmark
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def vecxtWorkload(bh: Blackhole): Unit =
58-
val dim = matDim.toInt
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// Create matrices and vector from the same data
60-
val matA = vecxt.matrix.Matrix(dataA, (dim, dim))
61-
val matB = vecxt.matrix.Matrix(dataB, (dim, dim))
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// Same representative linear algebra workload
64-
val step1 = matA + matB // Element-wise addition
65-
val step2 = step1.hadamard(matA) // Hadamard product
71+
val step1 = vecxtMatA + vecxtMatB // Element-wise addition
72+
val step2 = step1.hadamard(vecxtMatA) // Hadamard product
6673
val step3 = step2 * vectorData // Matrix-vector multiply
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val step4 = step3.fma(2.0, 1.0) // Element-wise transform
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val step5 = step4.norm // L2 norm

‎benchmark_vs_breeze/src/lazer.scala‎

Lines changed: 69 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,69 @@
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package vecxt.benchmark
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import org.openjdk.jmh.annotations.*
4+
import org.openjdk.jmh.infra.Blackhole
5+
import vecxt.BoundsCheck
6+
import scala.compiletime.uninitialized
7+
import vecxt.all.*
8+
import jdk.incubator.vector.VectorSpecies
9+
import jdk.incubator.vector.VectorOperators
10+
import jdk.incubator.vector.DoubleVector
11+
import breeze.linalg.*
12+
import vecxt.BoundsCheck.DoBoundsCheck.no
13+
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//% mill benchmark_vs_breeze.runJmh -jvmArgs --add-modules=jdk.incubator.vector
15+
@State(Scope.Thread)
16+
class LazerBenchmark extends BLASBenchmark:
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@Param(Array("500"))
19+
var matDim: String = uninitialized
20+
21+
var dataA: Array[Double] = uninitialized
22+
var dataB: Array[Double] = uninitialized
23+
var vectorData: Array[Double] = uninitialized
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25+
@Setup(Level.Invocation)
26+
def setup(): Unit =
27+
val dim = matDim.toInt
28+
dataA = randomDoubleArray(dim * dim)
29+
dataB = randomDoubleArray(dim * dim)
30+
vectorData = randomDoubleArray(dim)
31+
end setup
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33+
@Benchmark
34+
def breezeWorkload(bh: Blackhole): Unit =
35+
val dim = matDim.toInt
36+
// Create matrices and vector from the same data
37+
val matA = new DenseMatrix(dim, dim, dataA)
38+
val matB = new DenseMatrix(dim, dim, dataB)
39+
val vec = new DenseVector(vectorData)
40+
41+
// Representative linear algebra workload
42+
val step1 = matA + matB // Element-wise addition
43+
val step2 = step1 *:* matA // Hadamard product
44+
val step3 = step2 * vec // Matrix-vector multiply
45+
val step4 = step3.map(_ * 2.0 + 1.0) // Element-wise transform
46+
val step5 = breeze.linalg.norm(step4) // L2 norm
47+
val step7 = breeze.linalg.sum(step2) + step5 // Sum reduction
48+
bh.consume(step7)
49+
end breezeWorkload
50+
51+
@Benchmark
52+
def vecxtWorkload(bh: Blackhole): Unit =
53+
val dim = matDim.toInt
54+
// Create matrices and vector from the same data
55+
val matA = vecxt.matrix.Matrix(dataA, (dim, dim))
56+
val matB = vecxt.matrix.Matrix(dataB, (dim, dim))
57+
58+
// Same representative linear algebra workload
59+
val step1 = matA + matB // Element-wise addition
60+
val step2 = step1.hadamard(matA) // Hadamard product
61+
val step3 = step2 * vectorData // Matrix-vector multiply
62+
val step4 = step3.fma(2.0, 1.0) // Element-wise transform
63+
val step5 = step4.norm // L2 norm
64+
val step7 = step2.sum + step5 // Sum reduction
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66+
bh.consume(step7)
67+
end vecxtWorkload
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69+
end LazerBenchmark

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