Created by W.Langdon from gp-bibliography.bib Revision:1.7185
'code edits' p1 '6.7 million CPU hours .. (NERSC) Cori Supercomputer' nVidia P100, 1080Ti, V100: 3584, 3585, 5120 GPU cores.
p2 'up to 17 [mutations] contribute significantly to the optimization.' Fig 1 (GEVO) population of 256 LLVM IR edits, selection, crossover, mutation, (approx) 300 or 130 generations, 7 or 2 days. => NVPTX => PTX => fitness evaluation. mutation = copy, delete, move, replace, swap, replace the operand. 'strengthening a programmer understanding of system performance improvement opportunities.'
p3 stochastic simulation of 2D model of Lung epithelial cells and human immune system.
p4 'Over 90 percent of the GPU kernel runtime is spent moving T cells and spreading virus and inflammatory signals.'
'Fixing the random seed removes most of the stochasticity, but not all.' race condition (ie dont care...)
Three cases: with 1097, 1707, 1712 LLVM-IR instructions.
Validation not the same as training test (more onerous).
p5 variation between runs. 'some performance optimizations are GPU architecture-dependent.'
Post evolution 'Edit Minimization' removal of edits that speed up by less than 1 percent (reduce 1394 to 12) but twelve interact episatically with each other.
'code is robust against so many mutations while preserving required functionality.'
Fig 8: progressive improvement in performance (elite = 4/256 of population) even though genes interact.
p9 ' The developers were surprised that EC could synthesize code modifications with such large performance improvements' 'EC-driven optimization does not necessarily preserve exact program semantics, which is both a strengthand a limitation.'
p10 'There is no golden rule for finding optimal performance on GPUs.' 'EC can automate this search for counter-intuitive optimizations'",
Genetic Programming entries for Jhe-Yu Liou Muaaz Gul Awan Steven A Hofmeyr Stephanie Forrest Carole-Jean Wu