/* Optimized by Jonathan Hardwick (jch@cs.cmu.edu), 3/28/96 Compare to Linkpack.java. Optimizations performed: - added "final" modifier to performance-critical methods. - changed lines of the form "a[i] = a[i] + x" to "a[i] += x". - minimized array references using common subexpression elimination. - eliminated unused variables. - undid an unrolled loop. - added temporary 1D arrays to hold frequently-used columns of 2D arrays. - wrote my own abs() method See http://www.cs.cmu.edu/~jch/java/linpack.html for more details. Ported to Java by Reed Wade (wade@cs.utk.edu) 2/96 built using JDK 1.0 on solaris using "javac -O Linpack.java" Translated to C by Bonnie Toy 5/88 (modified on 2/25/94 to fix a problem with daxpy for unequal increments or equal increments not equal to 1. Jack Dongarra) */ import java.applet.Applet; import java.awt.*; import java.net.*; import java.io.*; import java.util.*; public class Linpack extends Applet { String applet_version = "LinpackJavaV2.0"; Button doit_b; String doit_b_string = "Press To Run Benchmark (may take a few moments)"; StatsGraph graph_c; Label mesg_l; Label os_l, cpu_l; Choice os_m, cpu_m; Label comments_l; TextField comments_e; Label name_l; TextField name_e; Label email_l; TextField email_e; Button submit_b; double mflops_result = 0.0; double residn_result = 0.0; double time_result = 0.0; double eps_result = 0.0; public void init () { setLayout(new BorderLayout()); Panel c1 = new Panel(); c1.setLayout(new BorderLayout()); doit_b = new Button(doit_b_string); c1.add("North", doit_b); doit_b.setForeground(Color.blue); graph_c = new StatsGraph(); c1.add("Center", graph_c); graph_c.resize(size().width, size().height); add("Center", c1); Panel c2 = new Panel(); c2.setLayout(new GridLayout(6,1)); mesg_l = new Label("If you would like to submit this timing fill in the boxes and hit Submit", Label.CENTER); c2.add(mesg_l); Panel c2_2 = new Panel(); os_l = new Label(" Operating System:"); c2_2.add(os_l); os_m = new Choice(); c2_2.add(os_m); os_m.addItem("Other"); os_m.addItem("Digital Unix (OSF)"); os_m.addItem("FreeBSD"); os_m.addItem("IRIX"); os_m.addItem("SunOS 4x"); os_m.addItem("Solaris 2x"); os_m.addItem("Linux"); os_m.addItem("Mac OS"); os_m.addItem("Windows95"); os_m.addItem("WindowsNT"); cpu_l = new Label(" CPU:"); c2_2.add(cpu_l); cpu_m = new Choice(); c2_2.add(cpu_m); cpu_m.addItem("Other"); cpu_m.addItem("Alpha"); cpu_m.addItem("Intel 386"); cpu_m.addItem("Intel 486"); cpu_m.addItem("Intel Pentium"); cpu_m.addItem("Intel P6"); cpu_m.addItem("Mac"); cpu_m.addItem("MIPS"); cpu_m.addItem("Sparc1"); cpu_m.addItem("Sparc2"); cpu_m.addItem("SparcIPX"); cpu_m.addItem("Sparc5"); cpu_m.addItem("Sparc10"); cpu_m.addItem("Sparc20"); cpu_m.addItem("UltraSparc"); c2.add(c2_2); Panel c2_3 = new Panel(); comments_l = new Label("Details:"); c2_3.add(comments_l); comments_e = new TextField(40); c2_3.add(comments_e); c2.add(c2_3); Panel c2_4 = new Panel(); name_l = new Label("Your Name:"); c2_4.add(name_l); name_e = new TextField(35); c2_4.add(name_e); c2.add(c2_4); Panel c2_5 = new Panel(); email_l = new Label("Email (required for submissions):"); c2_5.add(email_l); email_e = new TextField(25); c2_5.add(email_e); c2.add(c2_5); submit_b = new Button("Submit This Run"); submit_b.disable(); c2.add(submit_b); add("South", c2); graph_c.load_graph(); } final double abs (double d) { return (d >= 0) ? d : -d; } double second_orig = -1; double second() { if (second_orig==-1) { second_orig = System.currentTimeMillis(); } return (System.currentTimeMillis() - second_orig)/1000; } public void run_benchmark () { double a[][] = new double[200][201]; double b[] = new double[200]; double x[] = new double[200]; double cray,ops,total,norma,normx; double resid,time; double kf; int n,i,ntimes,info,lda,ldaa,kflops; int ipvt[] = new int[200]; //double mflops_result; //double residn_result; //double time_result; //double eps_result; lda = 201; ldaa = 200; cray = .056; n = 100; ops = (2.0e0*(n*n*n))/3.0 + 2.0*(n*n); norma = matgen(a,lda,n,b); time = second(); info = dgefa(a,lda,n,ipvt); dgesl(a,lda,n,ipvt,b,0); total = second() - time; for (i = 0; i < n; i++) { x[i] = b[i]; } norma = matgen(a,lda,n,b); for (i = 0; i < n; i++) { b[i] = -b[i]; } dmxpy(n,b,n,lda,x,a); resid = 0.0; normx = 0.0; for (i = 0; i < n; i++) { resid = (resid > abs(b[i])) ? resid : abs(b[i]); normx = (normx > abs(x[i])) ? normx : abs(x[i]); } eps_result = epslon((double)1.0); /* residn_result = resid/( n*norma*normx*eps_result ); time_result = total; mflops_result = ops/(1.0e6*total); return ("Mflops/s: " + mflops_result + " Time: " + time_result + " secs" + " Norm Res: " + residn_result + " Precision: " + eps_result); */ residn_result = resid/( n*norma*normx*eps_result ); residn_result += 0.005; // for rounding residn_result = (int)(residn_result*100); residn_result /= 100; time_result = total; time_result += 0.005; // for rounding time_result = (int)(time_result*100); time_result /= 100; mflops_result = ops/(1.0e6*total); mflops_result += 0.0005; // for rounding mflops_result = (int)(mflops_result*1000); mflops_result /= 1000; } final double matgen (double a[][], int lda, int n, double b[]) { double norma; int init, i, j; init = 1325; norma = 0.0; for (j = 0; j < n; j++) { for (i = 0; i < n; i++) { init = 3125*init % 65536; a[j][i] = (init - 32768.0)/16384.0; norma = (a[j][i] > norma) ? a[j][i] : norma; } } for (i = 0; i < n; i++) { b[i] = 0.0; } for (j = 0; j < n; j++) { for (i = 0; i < n; i++) { b[i] += a[j][i]; } } return norma; } /* dgefa factors a double precision matrix by gaussian elimination. dgefa is usually called by dgeco, but it can be called directly with a saving in time if rcond is not needed. (time for dgeco) = (1 + 9/n)*(time for dgefa) . on entry a double precision[n][lda] the matrix to be factored. lda integer the leading dimension of the array a . n integer the order of the matrix a . on return a an upper triangular matrix and the multipliers which were used to obtain it. the factorization can be written a = l*u where l is a product of permutation and unit lower triangular matrices and u is upper triangular. ipvt integer[n] an integer vector of pivot indices. info integer = 0 normal value. = k if u[k][k] .eq. 0.0 . this is not an error condition for this subroutine, but it does indicate that dgesl or dgedi will divide by zero if called. use rcond in dgeco for a reliable indication of singularity. linpack. this version dated 08/14/78. cleve moler, university of new mexico, argonne national lab. functions blas daxpy,dscal,idamax */ final int dgefa( double a[][], int lda, int n, int ipvt[]) { double[] col_k, col_j; double t; int j,k,kp1,l,nm1; int info; // gaussian elimination with partial pivoting info = 0; nm1 = n - 1; if (nm1 >= 0) { for (k = 0; k < nm1; k++) { col_k = a[k]; kp1 = k + 1; // find l = pivot index l = idamax(n-k,col_k,k,1) + k; ipvt[k] = l; // zero pivot implies this column already triangularized if (col_k[l] != 0) { // interchange if necessary if (l != k) { t = col_k[l]; col_k[l] = col_k[k]; col_k[k] = t; } // compute multipliers t = -1.0/col_k[k]; dscal(n-(kp1),t,col_k,kp1,1); // row elimination with column indexing for (j = kp1; j < n; j++) { col_j = a[j]; t = col_j[l]; if (l != k) { col_j[l] = col_j[k]; col_j[k] = t; } daxpy(n-(kp1),t,col_k,kp1,1, col_j,kp1,1); } } else { info = k; } } } ipvt[n-1] = n-1; if (a[(n-1)][(n-1)] == 0) info = n-1; return info; } /* dgesl solves the double precision system a * x = b or trans(a) * x = b using the factors computed by dgeco or dgefa. on entry a double precision[n][lda] the output from dgeco or dgefa. lda integer the leading dimension of the array a . n integer the order of the matrix a . ipvt integer[n] the pivot vector from dgeco or dgefa. b double precision[n] the right hand side vector. job integer = 0 to solve a*x = b , = nonzero to solve trans(a)*x = b where trans(a) is the transpose. on return b the solution vector x . error condition a division by zero will occur if the input factor contains a zero on the diagonal. technically this indicates singularity but it is often caused by improper arguments or improper setting of lda . it will not occur if the subroutines are called correctly and if dgeco has set rcond .gt. 0.0 or dgefa has set info .eq. 0 . to compute inverse(a) * c where c is a matrix with p columns dgeco(a,lda,n,ipvt,rcond,z) if (!rcond is too small){ for (j=0,j
= 1) { for (k = 0; k < nm1; k++) { l = ipvt[k]; t = b[l]; if (l != k){ b[l] = b[k]; b[k] = t; } kp1 = k + 1; daxpy(n-(kp1),t,a[k],kp1,1,b,kp1,1); } } // now solve u*x = y for (kb = 0; kb < n; kb++) { k = n - (kb + 1); b[k] /= a[k][k]; t = -b[k]; daxpy(k,t,a[k],0,1,b,0,1); } } else { // job = nonzero, solve trans(a) * x = b. first solve trans(u)*y = b for (k = 0; k < n; k++) { t = ddot(k,a[k],0,1,b,0,1); b[k] = (b[k] - t)/a[k][k]; } // now solve trans(l)*x = y if (nm1 >= 1) { for (kb = 1; kb < nm1; kb++) { k = n - (kb+1); kp1 = k + 1; b[k] += ddot(n-(kp1),a[k],kp1,1,b,kp1,1); l = ipvt[k]; if (l != k) { t = b[l]; b[l] = b[k]; b[k] = t; } } } } } /* constant times a vector plus a vector. jack dongarra, linpack, 3/11/78. */ final void daxpy( int n, double da, double dx[], int dx_off, int incx, double dy[], int dy_off, int incy) { int i,ix,iy; if ((n > 0) && (da != 0)) { if (incx != 1 || incy != 1) { // code for unequal increments or equal increments not equal to 1 ix = 0; iy = 0; if (incx < 0) ix = (-n+1)*incx; if (incy < 0) iy = (-n+1)*incy; for (i = 0;i < n; i++) { dy[iy +dy_off] += da*dx[ix +dx_off]; ix += incx; iy += incy; } return; } else { // code for both increments equal to 1 for (i=0; i < n; i++) dy[i +dy_off] += da*dx[i +dx_off]; } } } /* forms the dot product of two vectors. jack dongarra, linpack, 3/11/78. */ final double ddot( int n, double dx[], int dx_off, int incx, double dy[], int dy_off, int incy) { double dtemp; int i,ix,iy; dtemp = 0; if (n > 0) { if (incx != 1 || incy != 1) { // code for unequal increments or equal increments not equal to 1 ix = 0; iy = 0; if (incx < 0) ix = (-n+1)*incx; if (incy < 0) iy = (-n+1)*incy; for (i = 0;i < n; i++) { dtemp += dx[ix +dx_off]*dy[iy +dy_off]; ix += incx; iy += incy; } } else { // code for both increments equal to 1 for (i=0;i < n; i++) dtemp += dx[i +dx_off]*dy[i +dy_off]; } } return(dtemp); } /* scales a vector by a constant. jack dongarra, linpack, 3/11/78. */ final void dscal( int n, double da, double dx[], int dx_off, int incx) { int i,nincx; if (n > 0) { if (incx != 1) { // code for increment not equal to 1 nincx = n*incx; for (i = 0; i < nincx; i += incx) dx[i +dx_off] *= da; } else { // code for increment equal to 1 for (i = 0; i < n; i++) dx[i +dx_off] *= da; } } } /* finds the index of element having max. absolute value. jack dongarra, linpack, 3/11/78. */ final int idamax( int n, double dx[], int dx_off, int incx) { double dmax, dtemp; int i, ix, itemp=0; if (n < 1) { itemp = -1; } else if (n ==1) { itemp = 0; } else if (incx != 1) { // code for increment not equal to 1 dmax = abs(dx[0 +dx_off]); ix = 1 + incx; for (i = 1; i < n; i++) { dtemp = abs(dx[ix + dx_off]); if (dtemp > dmax) { itemp = i; dmax = dtemp; } ix += incx; } } else { // code for increment equal to 1 itemp = 0; dmax = abs(dx[0 +dx_off]); for (i = 1; i < n; i++) { dtemp = abs(dx[i + dx_off]); if (dtemp > dmax) { itemp = i; dmax = dtemp; } } } return (itemp); } /* estimate unit roundoff in quantities of size x. this program should function properly on all systems satisfying the following two assumptions, 1. the base used in representing dfloating point numbers is not a power of three. 2. the quantity a in statement 10 is represented to the accuracy used in dfloating point variables that are stored in memory. the statement number 10 and the go to 10 are intended to force optimizing compilers to generate code satisfying assumption 2. under these assumptions, it should be true that, a is not exactly equal to four-thirds, b has a zero for its last bit or digit, c is not exactly equal to one, eps measures the separation of 1.0 from the next larger dfloating point number. the developers of eispack would appreciate being informed about any systems where these assumptions do not hold. ***************************************************************** this routine is one of the auxiliary routines used by eispack iii to avoid machine dependencies. ***************************************************************** this version dated 4/6/83. */ final double epslon (double x) { double a,b,c,eps; a = 4.0e0/3.0e0; eps = 0; while (eps == 0) { b = a - 1.0; c = b + b + b; eps = abs(c-1.0); } return(eps*abs(x)); } /* purpose: multiply matrix m times vector x and add the result to vector y. parameters: n1 integer, number of elements in vector y, and number of rows in matrix m y double [n1], vector of length n1 to which is added the product m*x n2 integer, number of elements in vector x, and number of columns in matrix m ldm integer, leading dimension of array m x double [n2], vector of length n2 m double [ldm][n2], matrix of n1 rows and n2 columns */ final void dmxpy ( int n1, double y[], int n2, int ldm, double x[], double m[][]) { int j,i; // cleanup odd vector for (j = 0; j < n2; j++) { for (i = 0; i < n1; i++) { y[i] += x[j]*m[j][i]; } } } public boolean action(Event evt, Object arg) { if (evt.target==doit_b) { doit_b.setLabel("...running benchmark"); run_benchmark(); doit_b.setLabel(doit_b_string); //doit_b.disable(); submit_b.enable(); graph_c.setCurrentRun(mflops_result, residn_result, time_result, eps_result); graph_c.repaint(); return false; } else if (evt.target==submit_b) { //submit_b.disable(); try { String OS = os_m.getSelectedItem(); if (OS.equals("Other")) { OS = ""; } String CPU = cpu_m.getSelectedItem(); if (CPU.equals("Other")) { CPU = ""; } String months[] = { "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec" }; Date d = new Date(); String DATE = d.getDate() +" "+ months[d.getMonth()] +" "+ d.getYear(); String s = ("http://www.netlib.org/cgi-bin/email_icl/" +"generic_email?From=" +URLEncoder.encode(email_e.getText()) +"&To=linpackjava@netlib.org&" +"Subject=Linpack+Java+Submission&Message=" +URLEncoder.encode("\n\nname = "+name_e.getText()+"\n" +"OS = "+os_m.getSelectedItem()+"\n" +"CPU = "+cpu_m.getSelectedItem()+"\n" +"comments = "+comments_e.getText()+"\n" +"mflops = "+mflops_result+"\n" +"time = "+time_result+"\n" +"residn = "+residn_result+"\n" +"epsilon = "+eps_result+"\n\n" +"applet_version = "+applet_version+"\n\n" +mflops_result+" Mflop/s in "+time_result+" secs ; " +CPU+" " +OS+" " +comments_e.getText()+" ; "+DATE+", "+name_e.getText()+" ("+email_e.getText()+")\n\n") ); URL url = new URL(s); getAppletContext().showDocument(url); } catch (Exception e) { mesg_l.setText("!!submission failed for some reason"); } } return true; } }