Hi, I am a newbie in AFNI and this is my first time analysing fMRI data independently, so thank you in advance for your help. Please feel free to point out any folly that I have inadvertently fallen into, and let me know if I need to provide more info.

I am trying to run a similar analysis as one of those published in Mumford 2012 -- a separate GLM for each trial in preparation for MVPA. I built my scripts and preprocessing based on the MVPA tutorial from Brown University's Carney Institute for Brain Science.

I started with 16gb of RAM, and upgraded to 48gb, and still run into the same error of "current memory mallocated." I suspect that my problem is that I have 3600 trials...

Data and Design:
BOLD data: 90 trials for each of 40 categories (total 3600 trials), across 6 runs, data collected from 10 participants. Dimension:104x104x92 x 625 time points.
Data size: about 1.8gb for each participant (including all 6 runs, brain extracted)

Resources:
Software: Ubuntu 18.04.3 LTS, AFNI_19.3.18 'Nero'
Hardware: Intel Core i7-7700 CUP @ 3.6GHz x 8, RAM=48GB, data disk available space = 187.8GB

Bash Command
3dDeconvolve -input $fnames \ ← file names of the 6 BOLD run for this subject
-polort 1 \ ← terminal suggests minimum of 5, I did 1 here based on Brown's tutorial, is that wrong?
-local_times \
-GOFORIT 4 \
-num_stimts 40 \
-stim_times_IM 1 $stim_dir/${subj}_1_Snake.txt 'BLOCK(1,1)' -stim_label 1 Snake \
-stim_times_IM 2 $stim_dir/${subj}_2_Frog.txt 'BLOCK(1,1)' -stim_label 2 Frog \
... there are all together 40 lines of these. Calls stim timing file with 6 lines (1 for each run), 15 trials for each run, timing precision to 4 decimal
-bucket $reg_dir/id${subj}_bucket.nii

Issue (trimmed terminal output below)
1. as the script starts, it loads about 20gb into memory (I am guessing: 1.8gb data + 18.3gb the output says it needs for output briks?).
2. then it increases to about 38 gb.
3. 20 hours later:
- terminal says something about "need to compute the hard way"
- maxs out the RAM to 100% (47.xx gb)
- gives the "current memory mallocation" error
- started doing something about vertex/voxel loop (?) that puts out "0","1","2","3","4", each very slowly across the next few days.
4. I accidentally quitted (ctrl+C... sigh... when I tried to copy the error for the forum...) but terminal would not release the memory (still at 100% RAM used)
*My apologies about the vagueness in #3, I had to do this bit by memory... since I had to restart with no memory left to do anything... I am re-running it now, and I can post the actual error in ... 20 hours? (SIGH)

Four questions, if you don't mind:
1. The input data itself is not so large (1.8gb). Is this really ultimately a RAM issue? If so, how do I compute how much RAM do I actually need? Or did I do something wrong in the scripting?
2. Even though the 3dDeconvolve does stall, it output somethings before it stalls. What are those outputs? Are they usable?
3. 3dZcutup: I understand this to be a valid way to get around RAM issues. If I were to cut it up @ Z, should I first concatenate the 6 runs? I had read the 3dZcutup -help carefully, but I am still not entirely confident that I understand it well enough to put it back together correctly. Can you please recommend some tutorials for me?
4. I cannot find instructions to do 3dDeconvolve in a multithread manner to use my 8 cores. If I do 3dZcutup, can I then parallel the processes? E.g. core #1 runs slices 1, 9, 17... core #2 runs slices 2, 19, 18... etc. This should still need less RAM, right? I would be running 8 slices instead of all 92?

Terminal output (before the 20 hours described in issues step 3)
9006 is all ready for GLM now! @ Wed Jan 22 12:57:43 EST 2020
++ '-stim_times_IM 1 [[stim timing dir]]/9006_1_Snake.txt' will have 90 regressors
++ '-stim_times_IM 2 [[stim timing dir]]/9006_2_Frog.txt' will have 90 regressors
[[ and so on for a total of 40 stim categories]]
++ 3dDeconvolve: AFNI version=AFNI_19.3.18 (Dec 27 2019) [64-bit]
++ Authored by: B. Douglas Ward, et al.
++ current memory malloc-ated = 1,456,926 bytes (about 1.5 million)
++ loading dataset [[6 preprocessed, brain extracted BOLD runs]\
++ current memory malloc-ated = 1,614,150 bytes (about 1.6 million)
++ Auto-catenated input datasets treated as multiple imaging runs
++ Auto-catenated datasets start at: 0 625 1250 1875 2500 3125
++ STAT automask has 153313 voxels (out of 1274880 = 12.0%)
++ Skipping check for initial transients
*+ WARNING: Input polort=1; Longest run=625.0 s; Recommended minimum polort=5
++ -stim_times using TR=1 s for stimulus timing conversion
++ -stim_times using TR=1 s for any -iresp output datasets
++ [you can alter the -iresp TR via the -TR_times option]
++ -stim_times_IM 1 using LOCAL times
++ -stim_times_IM 2 using LOCAL times
[[ and so on for a total of 40 stim categories]]
++ Number of time points: 3750 (no censoring)
+ Number of parameters: 3612 [12 baseline ; 3600 signal]
++ Memory required for output bricks = 18,363,371,520 bytes (about 18 billion)
++ Wrote matrix values to file [[out put file name]]
++ ========= Things you can do with the matrix file =========
++ (a) Linear regression with ARMA(1,1) modeling of serial correlation:

3dREMLfit -matrix [output .xmat.1D] \
-input [[6 preprocessed, brain extracted BOLD runs]] \
-Rbuck [[output dir]] id9006_bucket_REMLvar -verb

++ N.B.: 3dREMLfit command above written to file [[output dir]]/id9006_bucket.REML_cmd
++ (b) Visualization/analysis of the matrix via ExamineXmat.R
++ (c) Synthesis of sub-model datasets using 3dSynthesize
++ ==========================================================
++ ----- Signal+Baseline matrix condition [X] (3750x3612): 1279.16 ++ OK ++
*+ WARNING: !! in Signal+Baseline matrix:
* Largest singular value=2.92141
* 84 singular values are less than cutoff=2.92141e-07
* Implies strong collinearity in the matrix columns!
++ Signal+Baseline matrix singular values:
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 8.22803e-10 6.99588e-09
7.61534e-09 1.17709e-08 1.44836e-08 1.65853e-08 1.69408e-08
1.86453e-08 2.11361e-08 2.13231e-08 2.43178e-08 2.59434e-08
[[and so on for a total of 723 lines]]
++ ----- Signal-only matrix condition [X] (3750x3600): 1233.42 ++ OK ++
*+ WARNING: !! in Signal-only matrix:
* Largest singular value=2.75718
* 84 singular values are less than cutoff=2.75718e-07
* Implies strong collinearity in the matrix columns!
++ Signal-only matrix singular values:
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 7.31057e-09 8.75017e-09
1.06977e-08 1.30859e-08 1.42085e-08 1.46287e-08 1.61204e-08
1.71607e-08 1.9407e-08 1.95557e-08 2.10651e-08 2.23834e-08
2.36478e-08 2.48074e-08 2.52718e-08 2.63005e-08 2.85352e-08
[[and so on for a total of 720 lines]]
++ ----- Baseline-only matrix condition [X] (3750x12): 1 ++ VERY GOOD ++
++ ----- polort-only matrix condition [X] (3750x12): 1 ++ VERY GOOD ++



Thank you again for your time in reading and considering to answer my questions, I really appreciate it!