Hi all

I also have an issue regarding processing speed while running my afni_proc.py on a participant's dataset. The voxel loop calculations took a while (see notes below).

++ N.B.: 3dREMLfit command above written to file stats.REML_cmd
++ (b) Visualization/analysis of the matrix via ExamineXmat.R
++ (c) Synthesis of sub-model datasets using 3dSynthesize
++ ==========================================================
++ Wrote matrix values to file X.nocensor.xmat.1D
++ ----- Signal+Baseline matrix condition [X] (1438x50): 4.56897 ++ VERY GOOD ++
++ ----- Signal-only matrix condition [X] (1438x12): 3.32982 ++ VERY GOOD ++
++ ----- Baseline-only matrix condition [X] (1438x38): 4.45074 ++ VERY GOOD ++
++ ----- stim_base-only matrix condition [X] (1438x6): 2.64395 ++ VERY GOOD ++
++ ----- polort-only matrix condition [X] (1438x32): 1.0138 ++ VERY GOOD ++
++ +++++ Matrix inverse average error = 7.89376e-16 ++ VERY GOOD ++
++ Matrix setup time = 15.18 s
++ current memory malloc-ated = 8,317,363,478 bytes (about 8.3 billion)
++ Calculations starting; elapsed time=238.874
++ voxel loop:0123456789.0123456789.0123456789.0123456789.0123456789.
++ Calculations finished; elapsed time=18149.402
++ Wrote bucket dataset into ./stats.CRD_001+tlrc.BRIK
+ created 25 FDR curves in bucket header
++ Wrote 3D+time dataset into ./fitts.CRD_001+tlrc.BRIK
++ Wrote 3D+time dataset into ./errts.CRD_001+tlrc.BRIK

Could you let me know the potential factors that might contribute to this please?

Cheers
David