Exemplo n.º 1
0
        public static Matrix <FieldType> GpuMultiply <FieldType, GpuStructType>(Matrix <FieldType> left, Matrix <FieldType> right) where FieldType : Field <FieldType>, IGpuCompatibleField <FieldType, GpuStructType>, new() where GpuStructType : struct
        {
            if (left.Width != right.Height)
            {
                throw new InvalidOperationException("Matrices of incompatible sizes can't be multiplied.");
            }

            IGpuStructManager <FieldType, GpuStructType> gpuStructManager = new FieldType().GetDefaultGpuStructManager();

            GpuStructType[,] resultArr = new GpuStructType[left.Rows, right.Columns];
            GpuStructType[,] leftArr   = new GpuStructType[left.Rows, left.Columns];
            GpuStructType[,] rightArr  = new GpuStructType[right.Rows, right.Columns];

            resultArr.AssignAll(gpuStructManager.GetStructDefaultValue());
            leftArr.AssignAll(ind => gpuStructManager.ToStruct(left[ind[0], ind[1]]));
            rightArr.AssignAll(ind => gpuStructManager.ToStruct(right[ind[0], ind[1]]));


            Alea.Gpu gpu = Alea.Gpu.Default;

            int threadCount = left.Rows * right.Columns;
            int blockDimX   = gpu.Device.Attributes.MaxThreadsPerBlock;           // Threads per block
            int gridDimX    = (int)Math.Ceiling((double)threadCount / blockDimX); // Blocks per thread

            LaunchParam lp = new LaunchParam(gridDimX, blockDimX);

            gpu.Launch(multiplicationKernel, lp, leftArr, rightArr, resultArr, gpuStructManager.GetStructAddition(), gpuStructManager.GetStructMultiplication());

            FieldType[,] fieldResultArr = new FieldType[resultArr.GetLength(0), resultArr.GetLength(1)];
            fieldResultArr.AssignAll(ind => gpuStructManager.ToClass(resultArr[ind[0], ind[1]]));

            return(new Matrix <FieldType>(fieldResultArr));
        }
Exemplo n.º 2
0
 public Model(Alea.Gpu gpu, Reader.Reader reader)
 {
     GPU            = gpu;
     LearningReader = reader;
 }