From cube-lovers-errors@mc.lcs.mit.edu Wed Jan 14 19:00:40 1998 Return-Path: Received: from sun30.aic.nrl.navy.mil by mc.lcs.mit.edu (8.8.1/mc) with SMTP id TAA05544; Wed, 14 Jan 1998 19:00:40 -0500 (EST) Precedence: bulk Errors-To: cube-lovers-errors@mc.lcs.mit.edu Mail-from: From cube-lovers-request@life.ai.mit.edu Wed Jan 14 13:43:31 1998 Date: Wed, 14 Jan 1998 13:42:20 -0500 (Eastern Standard Time) From: Jerry Bryan Subject: Performance Analyzers for Cube (and other) Programs To: cube-lovers@ai.mit.edu Reply-To: Jerry Bryan Message-Id: [Moderator's note: Please reply directly to Jerry.] This is a little off topic, but many cube searching programs run for dozens or hundreds of hours and we are always interested in speeding them up. The best speed ups usually come from algorithm improvements, but I am also interested in more mundane program improvements. Through the years, I have used various tools, usually for FORTRAN, usually on mainframes, which will analyze a running program, telling you where (which routines, which lines of source code) the program is spending its time. I am now running mostly C programs, mostly on a PC. I confess I am clueless as to what performance analysis tools might be available in this environment. (I use Borland C++ if it matters.) Any suggestions would be gratefully accepted. = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = Robert G. Bryan (Jerry Bryan) jbryan@pstcc.cc.tn.us Pellissippi State (423) 539-7198 10915 Hardin Valley Road (423) 694-6435 (fax) P.O. Box 22990 Knoxville, TN 37933-0990