コード例 #1
0
        static (double[] EigenVals, MultidimensionalArray EigenVect) EigenspaceSymmInternal(this IMatrix Inp, bool ComputeVectors)
        {
            if (Inp.NoOfCols != Inp.NoOfRows)
            {
                throw new ArgumentException("Not supported for non-symmetrical matrices.");
            }
            int N = Inp.NoOfRows;

            int JOBZ = ComputeVectors ? 'V' : 'N';
            // 'N':  Compute eigenvalues only;
            // 'V':  Compute eigenvalues and eigenvectors.

            int UPLO = 'L';

            // 'U':  Upper triangle of A is stored;
            // 'L':  Lower triangle of A is stored.

            unsafe {
                double[] InpBuffer             = TempBuffer.GetTempBuffer(out int RefInp, N * N);
                double[] Eigis                 = new double[N];
                MultidimensionalArray EigiVect = ComputeVectors ? MultidimensionalArray.Create(N, N) : null;

                fixed(double *pInp = InpBuffer, pEigis = Eigis)
                {
                    CopyToUnsafeBuffer(Inp, pInp, true);

                    int LDA = N;
                    int info;

                    // phase 1: work size estimation
                    double WorkSize;
                    int    LWORK = -1; // triggers estimation

                    LAPACK.F77_LAPACK.DSYEV_(ref JOBZ, ref UPLO, ref N, pInp, ref LDA, pEigis, &WorkSize, ref LWORK, out info);
                    if (info != 0)
                    {
                        TempBuffer.FreeTempBuffer(RefInp);
                        throw new ArithmeticException("LAPACK DSYEV (symmetrical matrix eigenvalues) returned info " + info);
                    }

                    LWORK = (int)WorkSize;

                    // phase 2: computation
                    double[] WorkBuffer = TempBuffer.GetTempBuffer(out int RefWork, LWORK * 1);
                    fixed(double *pWork = WorkBuffer)
                    {
                        LAPACK.F77_LAPACK.DSYEV_(ref JOBZ, ref UPLO, ref N, pInp, ref LDA, pEigis, pWork, ref LWORK, out info);
                        TempBuffer.FreeTempBuffer(RefWork);
                        if (info != 0)
                        {
                            TempBuffer.FreeTempBuffer(RefInp);
                            throw new ArithmeticException("LAPACK DSYEV (symmetrical matrix eigenvalues) returned info " + info);
                        }

                        if (EigiVect != null)
                        {
                            CopyFromUnsafeBuffer(EigiVect, pInp, true);
                        }
                    }
                }

                TempBuffer.FreeTempBuffer(RefInp);


                return(Eigis, EigiVect);
            }
        }
コード例 #2
0
        public static void MultiplyTest0()         // one summation index
        {
            foreach (int C in new int[] { 2, 60 }) // test unrolling and standard path

            {
                int I = 120;
                int J = 21;
                int K = 40;


                MultidimensionalArray A = MultidimensionalArray.Create(I, C, K);
                MultidimensionalArray B = MultidimensionalArray.Create(K, C, J);

                Console.WriteLine("number of operands in A: " + A.Length);
                Console.WriteLine("number of operands in B: " + B.Length);

                MultidimensionalArray ResTst1 = MultidimensionalArray.Create(J, K, I);
                MultidimensionalArray ResTst2 = MultidimensionalArray.Create(J, K, I);
                MultidimensionalArray ResChck = MultidimensionalArray.Create(J, K, I);

                // fill operands with random values
                Random rnd = new Random();
                A.ApplyAll(x => rnd.NextDouble());
                B.ApplyAll(x => rnd.NextDouble());

                double alpha = 0.99;
                double beta  = 0;

                Stopwatch sw = new Stopwatch();


                // tensorized multiplication:
                sw.Reset();
                sw.Start();
                ResTst1.Multiply(alpha, A, B, beta, "jki", "ick", "kcj");
                ResTst2.Multiply(alpha, B, A, beta, "jki", "kcj", "ick");
                sw.Stop();

                Console.WriteLine("runtime of tensorized multiplication: " + sw.ElapsedMilliseconds + " millisec.");

                // old-fashioned equivalent with loops:
                double errsum = 0;
                sw.Reset();
                sw.Start();
                for (int i = 0; i < I; i++)
                {
                    for (int j = 0; j < J; j++)
                    {
                        for (int k = 0; k < K; k++)
                        {
                            // summation:
                            double sum = 0;
                            for (int c = 0; c < C; c++)
                            {
                                sum += A[i, c, k] * B[k, c, j];
                            }

                            ResChck[j, k, i] = sum * alpha + ResChck[j, k, i] * beta;

                            errsum += Math.Abs(ResTst1[j, k, i] - ResChck[j, k, i]);
                            errsum += Math.Abs(ResTst2[j, k, i] - ResChck[j, k, i]);
                        }
                    }
                }
                sw.Stop();

                Console.WriteLine("runtime of loop multiplication: " + sw.ElapsedMilliseconds + " millisec.");
                Console.WriteLine("total error: " + errsum);

                double thres = 1.0e-13;
                Assert.IsTrue(errsum < thres);
            }
        }
コード例 #3
0
        public static void MultiplyTest3()         // two summation indices (k,r)
        {
            foreach (int K in new int[] { 2, 21 }) // test unrolling and standard path
            {
                int I = 12;
                int M = 43;
                int N = 63;
                int R = 21;

                MultidimensionalArray A = MultidimensionalArray.Create(I, R, K, M);
                MultidimensionalArray B = MultidimensionalArray.Create(I, K, N, R);

                Console.WriteLine("number of operands in A: " + A.Length);
                Console.WriteLine("number of operands in B: " + B.Length);

                MultidimensionalArray ResTst1 = MultidimensionalArray.Create(I, M, N);
                MultidimensionalArray ResTst2 = MultidimensionalArray.Create(I, M, N);
                MultidimensionalArray ResChck = MultidimensionalArray.Create(I, M, N);

                // fill operands with random values
                Random rnd = new Random();
                A.ApplyAll(x => rnd.NextDouble());
                B.ApplyAll(x => rnd.NextDouble());
                ResTst1.ApplyAll(x => rnd.NextDouble());
                ResChck.Set(ResTst1);
                ResTst2.Set(ResTst1);


                double alpha = 0.67;
                double beta  = 1.3;


                // tensorized multiplication:
                Stopwatch TenMult = new Stopwatch();
                TenMult.Start();
                ResTst1.Multiply(alpha, A, B, beta, "imn", "irkm", "iknr");
                TenMult.Stop();
                ResTst2.Multiply(alpha, B, A, beta, "imn", "iknr", "irkm");
                Console.WriteLine("runtime of tensorized multiplication: " + TenMult.ElapsedMilliseconds + " millisec.");

                // comparison code
                Stopwatch RefMult = new Stopwatch();
                RefMult.Start();

                double errSum = 0;
                for (int i = 0; i < I; i++)
                {
                    for (int n = 0; n < N; n++)
                    {
                        for (int m = 0; m < M; m++)
                        {
                            // summation:
                            double sum = 0;
                            for (int r = 0; r < R; r++)
                            {
                                for (int k = 0; k < K; k++)
                                {
                                    sum += A[i, r, k, m] * B[i, k, n, r];
                                }
                            }

                            ResChck[i, m, n] = sum * alpha + ResChck[i, m, n] * beta;

                            errSum += Math.Abs(ResTst1[i, m, n] - ResChck[i, m, n]);
                            errSum += Math.Abs(ResTst2[i, m, n] - ResChck[i, m, n]);
                        }
                    }
                }
                RefMult.Stop();
                Console.WriteLine("runtime of loop multiplication: " + RefMult.ElapsedMilliseconds + " millisec.");

                Console.WriteLine("total error: " + errSum);

                double thres = 1.0e-6;
                Assert.IsTrue(errSum < thres);
            }
        }
コード例 #4
0
        public static void MultiplyTrafoTest0()   // two summation indices (k,r)
        {
            foreach (int K in new int[] { 210 })  // test unrolling and standard path
            {
                int I = 120;
                int M = 43;

                MultidimensionalArray A = MultidimensionalArray.Create(I, K, 2 * M);
                MultidimensionalArray B = MultidimensionalArray.Create(2 * M, K);;

                Console.WriteLine("number of operands in A: " + A.Length);
                Console.WriteLine("number of operands in B: " + B.Length);

                int[] mTrafo = new int[M];

                MultidimensionalArray ResTst1 = MultidimensionalArray.Create(I, M);
                MultidimensionalArray ResTst2 = MultidimensionalArray.Create(I, M);
                MultidimensionalArray ResChck = MultidimensionalArray.Create(I, M);

                // fill operands with random values
                Random rnd = new Random();
                A.ApplyAll(x => rnd.NextDouble());
                B.ApplyAll(x => rnd.NextDouble());

                ResTst1.ApplyAll(x => rnd.NextDouble());
                ResChck.Set(ResTst1);
                ResTst2.Set(ResTst1);

                for (int m = 0; m < M; m++)
                {
                    mTrafo[m] = rnd.Next(2 * M);
                    //mTrafo[m] = m;
                    Debug.Assert(mTrafo[m] < 2 * M);
                }


                double alpha = 0.67;
                double beta  = 1.3;

                var mp1 = MultidimensionalArray.MultiplyProgram.Compile("im", "ikT(m)", "T(m)k", true);
                var mp2 = MultidimensionalArray.MultiplyProgram.Compile("im", "T(m)k", "ikT(m)", true);


                // tensorized multiplication:
                Stopwatch TenMult = new Stopwatch();
                TenMult.Start();
                ResTst1.Multiply(alpha, A, B, beta, ref mp1, mTrafo);
                TenMult.Stop();
                ResTst2.Multiply(alpha, B, A, beta, ref mp2, mTrafo);
                Console.WriteLine("runtime of tensorized multiplication: " + TenMult.ElapsedMilliseconds + " millisec.");

                // comparison code
                Stopwatch RefMult = new Stopwatch();
                RefMult.Start();

                double errSum = 0;
                for (int i = 0; i < I; i++)
                {
                    for (int m = 0; m < M; m++)
                    {
                        int m_trf = mTrafo[m];

                        // summation:
                        double sum = 0;
                        for (int k = 0; k < K; k++)
                        {
                            sum += A[i, k, m_trf] * B[m_trf, k];
                        }

                        ResChck[i, m] = sum * alpha + ResChck[i, m] * beta;

                        errSum += Math.Abs(ResTst1[i, m] - ResChck[i, m]);
                        errSum += Math.Abs(ResTst2[i, m] - ResChck[i, m]);
                    }
                }


                RefMult.Stop();
                Console.WriteLine("runtime of loop multiplication: " + RefMult.ElapsedMilliseconds + " millisec.");

                Console.WriteLine("total error: " + errSum);

                double thres = 1.0e-6;
                Assert.IsTrue(errSum < thres);
            }
        }
コード例 #5
0
        public static void MultiplyTest2()   // no summation, only tenzorization
        {
            int I = 125;
            int K = 21;
            int M = 43;
            int N = 63;

            MultidimensionalArray A = MultidimensionalArray.Create(I, K, M);
            MultidimensionalArray B = MultidimensionalArray.Create(I, K, N);

            Console.WriteLine("number of operands in A: " + A.Length);
            Console.WriteLine("number of operands in B: " + B.Length);

            MultidimensionalArray ResTst1 = MultidimensionalArray.Create(I, K, M, N);
            MultidimensionalArray ResTst2 = MultidimensionalArray.Create(I, K, M, N);
            MultidimensionalArray ResChck = MultidimensionalArray.Create(I, K, M, N);

            // fill operands with random values
            Random rnd = new Random();

            A.ApplyAll(x => rnd.NextDouble());
            B.ApplyAll(x => rnd.NextDouble());


            // tensorized multiplication:
            Stopwatch TenMult = new Stopwatch();

            TenMult.Start();
            ResTst1.Multiply(1.0, A, B, 0.0, "ikmn", "ikm", "ikn");
            TenMult.Stop();
            ResTst2.Multiply(1.0, B, A, 0.0, "ikmn", "ikn", "ikm");
            Console.WriteLine("runtime of tensorized multiplication: " + TenMult.ElapsedMilliseconds + " millisec.");

            // comparison code
            Stopwatch RefMult = new Stopwatch();

            RefMult.Start();

            double errSum = 0;

            for (int i = 0; i < I; i++)
            {
                for (int k = 0; k < K; k++)
                {
                    for (int n = 0; n < N; n++)
                    {
                        for (int m = 0; m < M; m++)
                        {
                            ResChck[i, k, m, n] = A[i, k, m] * B[i, k, n];
                            errSum += Math.Abs(ResChck[i, k, m, n] - ResTst1[i, k, m, n]);
                            errSum += Math.Abs(ResChck[i, k, m, n] - ResTst2[i, k, m, n]);
                        }
                    }
                }
            }
            RefMult.Stop();
            Console.WriteLine("runtime of loop multiplication: " + RefMult.ElapsedMilliseconds + " millisec.");

            Console.WriteLine("total error: " + errSum);

            double thres = 1.0e-13;

            Assert.IsTrue(errSum < thres);
        }