R session is aborted when I assign one matrix to another - r

Question

I just got a new Acer Swift laptop and installed ubuntu 20.04 on it. I installed R.4.0.3 and Rstudio 1.2.5042
I tried to run a script that is running without problems on my old computer. R crashes and Rstudio aborts when I assign one matrix to another. I tried increasing R memory (it is inf now) and doing the same assignment using matrix subsets. It still crashes. R session is also aborted if I skip the matrix assignment and just try to do other manipulations with the matrix ext_data.df
FYI: data.input is a matrix 33538 x 11366. ext_data.df is properly initialiozed. It is only at the assignment
ext_data.df[common_genes,] = data.input[common_genes,]
that the crash happens.
ext_data.df=matrix(0,dim(gene_list)[1],dim(data.input)[2])
rownames(ext_data.df) = gene_list$X2
colnames(ext_data.df) <- colnames(data.input)
common_genes = intersect(gene_list$X2,rownames(data.input))
ext_data.df[common_genes,] = data.input[common_genes,]
sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.1 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/liblapack.so.3
locale:
[1] LC_CTYPE=en_SG.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_SG.UTF-8 LC_COLLATE=en_SG.UTF-8
[5] LC_MONETARY=en_SG.UTF-8 LC_MESSAGES=en_SG.UTF-8
[7] LC_PAPER=en_SG.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_SG.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] tensorflow_2.2.0 kknn_1.3.1 plotly_4.9.3 viridis_0.5.1
[5] viridisLite_0.3.0 KernelKnn_1.1.0 forcats_0.5.0 stringr_1.4.0
[9] dplyr_1.0.3 purrr_0.3.4 readr_1.4.0 tidyr_1.1.2
[13] tibble_3.0.5 tidyverse_1.3.0 keras_2.3.0.0 ggpubr_0.4.0
[17] ggplot2_3.3.3 ggsci_2.9 class_7.3-17 Seurat_3.2.3
loaded via a namespace (and not attached):
[1] readxl_1.3.1 backports_1.2.1 plyr_1.8.6
[4] igraph_1.2.6 lazyeval_0.2.2 splines_4.0.3
[7] listenv_0.8.0 scattermore_0.7 tfruns_1.4
[10] digest_0.6.27 htmltools_0.5.1.1 fansi_0.4.2
[13] magrittr_2.0.1 tensor_1.5 cluster_2.1.0
[16] ROCR_1.0-11 openxlsx_4.2.3 globals_0.14.0
[19] modelr_0.1.8 matrixStats_0.57.0 askpass_1.1
[22] colorspace_2.0-0 rvest_0.3.6 rappdirs_0.3.1
[25] ggrepel_0.9.1 haven_2.3.1 crayon_1.3.4
[28] jsonlite_1.7.2 spatstat_1.64-1 spatstat.data_1.7-0
[31] zeallot_0.1.0 survival_3.2-7 zoo_1.8-8
[34] glue_1.4.2 polyclip_1.10-0 gtable_0.3.0
[37] leiden_0.3.7 car_3.0-10 future.apply_1.7.0
[40] abind_1.4-5 scales_1.1.1 DBI_1.1.1
[43] rstatix_0.6.0 miniUI_0.1.1.1 Rcpp_1.0.6
[46] xtable_1.8-4 reticulate_1.18 foreign_0.8-81
[49] rsvd_1.0.3 umap_0.2.7.0 htmlwidgets_1.5.3
[52] httr_1.4.2 RColorBrewer_1.1-2 ellipsis_0.3.1
[55] ica_1.0-2 pkgconfig_2.0.3 uwot_0.1.10
[58] dbplyr_2.0.0 deldir_0.2-9 tidyselect_1.1.0
[61] rlang_0.4.10 reshape2_1.4.4 later_1.1.0.1
[64] munsell_0.5.0 cellranger_1.1.0 tools_4.0.3
[67] cli_2.2.0 generics_0.1.0 broom_0.7.3
[70] ggridges_0.5.3 fastmap_1.1.0 goftest_1.2-2
[73] fs_1.5.0 fitdistrplus_1.1-3 zip_2.1.1
[76] RANN_2.6.1 pbapply_1.4-3 future_1.21.0
[79] nlme_3.1-151 whisker_0.4 mime_0.9
[82] xml2_1.3.2 compiler_4.0.3 rstudioapi_0.13
[85] curl_4.3 png_0.1-7 ggsignif_0.6.0
[88] spatstat.utils_2.0-0 reprex_0.3.0 stringi_1.5.3
[91] RSpectra_0.16-0 lattice_0.20-41 Matrix_1.3-2
[94] vctrs_0.3.6 pillar_1.4.7 lifecycle_0.2.0
[97] lmtest_0.9-38 RcppAnnoy_0.0.18 data.table_1.13.6
[100] cowplot_1.1.1 irlba_2.3.3 httpuv_1.5.5
[103] patchwork_1.1.1 R6_2.5.0 promises_1.1.1
[106] KernSmooth_2.23-18 gridExtra_2.3 rio_0.5.16
[109] parallelly_1.23.0 codetools_0.2-18 MASS_7.3-53
[112] assertthat_0.2.1 openssl_1.4.3 withr_2.4.0
[115] sctransform_0.3.2 mgcv_1.8-33 parallel_4.0.3
[118] hms_1.0.0 grid_4.0.3 rpart_4.1-15
[121] carData_3.0-4 Rtsne_0.15 shiny_1.6.0
[124] lubridate_1.7.9.2 base64enc_0.1-3
Could you please help me solve the problem?
Thank you very much!

Answer 1

Could it be that you are using 32 bit version of R?
32 bit applications can only access a maximum of 4 Gigs of memory.
Can you try the following
.Machine$sizeof.pointer
it should return 8 if you are using 64 bit R

Answer 2

Update: It is clearly a memory problem. When I try to do the assignment
ext_data.df[common_genes,1:1000]=data.input[common_genes, 1:1000] it works.
I monitored the usage with mem_used() and found that it works up to 7.8GB (it happens for ext_data.df[common_genes,1:3000]=data.input[common_genes, 1:3000].
At 8GB, the R session gets aborted. How can I increase the memory above 8GB. In my old laptop (MacBook Pro), the mem_used was 8.21GB for the whole assignment.
I have to note that I use Sys.setenv('R_MAX_MEM_SIZE'=64000000000)
and Sys.setenv('R_MAX_VSIZE'=64000000000) in the beginning of my script.

Answer 3

Maybe you can try increasing the memory via memory.limit().
You can refer to this stackoverflow thread for more information:
Increasing (or decreasing) the memory available to R processes