From 383984adb69aceb4ab885920557f8890382ecd43 Mon Sep 17 00:00:00 2001 From: Don Armstrong Date: Wed, 15 Jun 2016 13:23:33 -0700 Subject: [PATCH] switch to utf8 bases --- posts/supercomputer_wishlist.mdwn | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/posts/supercomputer_wishlist.mdwn b/posts/supercomputer_wishlist.mdwn index 7d829ef..9969907 100644 --- a/posts/supercomputer_wishlist.mdwn +++ b/posts/supercomputer_wishlist.mdwn @@ -1,8 +1,8 @@ [[!meta title="Bioinformatic Supercomputer Wishlist"]] Many bioinformatic problems require large amounts of memory and -processor time to complete. For example, running WGCNA across 10^6 CpG -sites requires 10^6 choose 2 or 10^13 comparisons, which needs 10 TB +processor time to complete. For example, running WGCNA across 10⁶ CpG +sites requires 10⁶ choose 2 or 10¹³ comparisons, which needs 10 TB to store the resulting matrix. While embarrassingly parallel, the dataset upon which the regressions are calculated is very large, and cannot fit into main memory of most existing supercomputers, which are @@ -10,11 +10,11 @@ often tuned for small-data fast-interconnect problems. Another problem which I am interested in is computing ancestral trees from whole human genomes. This involves running maximum likelihood -calculations across 10^9 bases and thousands of samples. The matrix +calculations across 10⁹ bases and thousands of samples. The matrix itself could potentially take 1 TB, and calculating the likelihood across that many positions is computationally expensive. Furthermore, an exhaustive search of trees for 2000 individuals requires 2000!! -comparisons, or 10^2868; even searching a small fraction of that +comparisons, or 10²⁸⁶⁸; even searching a small fraction of that subspace requires lots of computational time. Some things that a future supercomputer could have that would enable -- 2.39.2