For MatLab users, this currently free beta is IMO worth checking out: QLA - Quick Linear Algebra library. http://massiveanalytics.com/ Info document: http://www.accelereyes.com/content/qla_files/qla_doc.pdf Ran realistic intra-day matrices of SP500, about 36% speed savings. Will be especially helpful for those running large linear regressions/least sq's etc. Anything with spectral concentration of data, for that matter. Speedup vs data loss (accuracy) seems well-balanced using default error tolerance, but just started tinkering, so no definitive conclusions yet. As of this release, looks like representation via dense matrix only. Sparse in upcoming release? Simple to install/use. An example svd I ran: >> clear all n=150; m=1500; mat=zeros(m,m); for i=1:n mat(i,: )=[1:m]*i; end u=zeros(m,m); s=zeros(m,m); v=zeros(m,m); tic; for i=1:n [u,s,v] = svd(mat); end normal_time = toc/n; u=zeros(m,1); s=zeros(m,1); v=zeros(m,m); tic; for i=1:n [u,s,v] = qsvd(mat); end q_time = toc/n; fprintf('Normal Matlab: %f\nQLA: %f\nSpeedup:%f\n',normal_time,q_time,normal_time/q_time) Normal Matlab: 9.382163 QLA: 0.029765 Speedup: 315.208249 315x!!! With properly vectorized implementation, cha-ching? Using r2009b, XPProSP3. Let me know what you guys find out.