Upload test.swift
Browse files- test.swift +104 -0
test.swift
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import Foundation
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import Accelerate
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import MetalPerformanceShaders
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// Sizes of the matrices: C = A x B.
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private let rowsA = 3
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private let columnsA = 4
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private let rowsB = columnsA
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private let columnsB = 2
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private let rowsC = rowsA
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private let columnsC = columnsB
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private var device: MTLDevice!
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private var commandQueue: MTLCommandQueue!
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private var matrixMultiplication: MPSMatrixMultiplication!
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private var matrixA: MPSMatrix!
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private var matrixB: MPSMatrix!
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private var matrixC: MPSMatrix!
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private var arrayA = [Float](repeating: 0, count: rowsA * columnsA)
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private var arrayB = [Float](repeating: 0, count: rowsB * columnsB * 2)
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private var arrayC = [Float](repeating: 0, count: rowsC * columnsC)
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func run() {
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randomizeArrays()
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initMPS()
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}
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private func randomizeArrays() {
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// Fill up A and B with random floating point numbers (between -1 and +1).
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for i in 0..<arrayA.count {
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arrayA[i] = Float(i)
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}
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for i in 0..<arrayB.count {
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arrayB[i] = Float(i)
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}
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print(arrayB)
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}
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private func initMPS() {
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device = MTLCreateSystemDefaultDevice()
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guard device != nil else {
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fatalError("Error: This device does not support Metal")
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}
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guard MPSSupportsMTLDevice(device) else {
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fatalError("Error: This device does not support Metal Performance Shaders")
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}
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commandQueue = device.makeCommandQueue()
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matrixMultiplication = MPSMatrixMultiplication(device: device, transposeLeft: false, transposeRight: false, resultRows: rowsC, resultColumns: columnsC, interiorColumns: columnsA, alpha: 1, beta: 0)
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// For optimal speed, we should use the recommended row stride.
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//let rowBytesA = MPSMatrixDescriptor.rowBytes(fromColumns: columnsA, dataType: .float32)
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//print("preferred stride \(rowBytesA), my stride \(columnsA * MemoryLayout<Float>.stride)")
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// The contents of the arrays are copied into the MTLBuffers. Note that we
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// don't copy arrayC into bufferC because it's just zeros (arrayC is only
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// used to store the results of the BLAS matrix multiply).
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let bufferA = device.makeBuffer(bytes: arrayA, length: rowsA * columnsA * MemoryLayout<Float>.stride, options: [])
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let bufferB = device.makeBuffer(bytes: arrayB, length: rowsB * columnsB * MemoryLayout<Float>.stride * 2, options: [])
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let bufferC = device.makeBuffer(length: rowsC * columnsC * MemoryLayout<Float>.stride, options: [])
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let descA = MPSMatrixDescriptor(dimensions: rowsA, columns: columnsA, rowBytes: columnsA * MemoryLayout<Float>.stride, dataType: .float32)
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let descB = MPSMatrixDescriptor(dimensions: rowsB, columns: columnsB, rowBytes: columnsB * MemoryLayout<Float>.stride, dataType: .float32)
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let descC = MPSMatrixDescriptor(dimensions: rowsC, columns: columnsC, rowBytes: columnsC * MemoryLayout<Float>.stride, dataType: .float32)
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matrixA = MPSMatrix(buffer: bufferA!, descriptor: descA)
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matrixB = MPSMatrix(buffer: bufferB!, offset: 0, descriptor: descB)
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matrixC = MPSMatrix(buffer: bufferC!, descriptor: descC)
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var commandBuffer = commandQueue.makeCommandBuffer()!
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matrixMultiplication.encode(commandBuffer: commandBuffer, leftMatrix: matrixA, rightMatrix: matrixB, resultMatrix: matrixC)
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commandBuffer.commit()
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commandBuffer.waitUntilCompleted()
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var contents = bufferC!.contents();
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var count = rowsA * columnsB;
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var typedPointer = contents.bindMemory(to: Float.self, capacity: count)
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var bufferedPointer = UnsafeBufferPointer(start: typedPointer, count: count)
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print(Array(bufferedPointer))
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print("Offsetted")
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matrixA = MPSMatrix(buffer: bufferA!, descriptor: descA)
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matrixB = MPSMatrix(buffer: bufferB!, offset: 4 * 2 * 4, descriptor: descB)
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matrixC = MPSMatrix(buffer: bufferC!, descriptor: descC)
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commandBuffer = commandQueue.makeCommandBuffer()!
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matrixMultiplication.encode(commandBuffer: commandBuffer, leftMatrix: matrixA, rightMatrix: matrixB, resultMatrix: matrixC)
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commandBuffer.commit()
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commandBuffer.waitUntilCompleted()
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contents = bufferC!.contents();
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count = rowsA * columnsB;
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typedPointer = contents.bindMemory(to: Float.self, capacity: count)
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bufferedPointer = UnsafeBufferPointer(start: typedPointer, count: count)
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print(Array(bufferedPointer))
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}
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run()
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