benchmark_shape_old.R

## This script compares different tilesizes, number of streams and gemm shapes for MMAGPU. 
# We assume a population with 10k individuals and 1000k SNPs.

library(miraculix)
# Global RFutils options
RFoptions(install="none", cores=12, helpinfo=FALSE)
RFoptions(centered=FALSE, normalized=FALSE, la_mode=LA_GPU)

# Number of individuals
n <- 10000
# Number of SNPs
snps <- 1e6
# Matrices for time measurements
tiles <- seq(512, by=256, to=2048) # 256 is smallest possible step
streams <- c(6) # seq(4, by=1, to=12)
shapes <- 0:5
tile_time <- array(NA, c(length(shapes), length(tiles), length(streams)))
average_matrix <- 10
divisor <- 1000

# Simulate population
SNPs <- matrix(sample(1, n/divisor * snps, replace=T), ncol=n/divisor)

# MMA1Bit options
RFoptions(snpcoding=MMAGPU)
cat("snpcoding=MMAGPU\n")

Z <- miraculix::genomicmatrix(snps, n)
for (j in 0:(divisor-1)) {
  fillGeno(Z, (1:(n/divisor)) + n/divisor * j, SNPs)
}

for (shape in 1:length(shapes)) {
  for (tile in 1:length(tiles)) {
    print(tile)
    for (stream in 1:length(streams)) {
      # limit global memory to value necessary on my machine (RTX 2070)
      if (streams[stream]*(tiles[tile]^2*4 + (snps/2) * tiles[tile]) <= 8361213952*0.8) {
        tile_time[shape,tile,stream] <- 0
        for (i in 1:average_matrix) {
          Sys.sleep(0.2) # slight time buffer
          # calculation relationship matrix
          tile_time[shape,tile,stream] <- tile_time[shape,tile,stream] + system.time({
            G <- miraculix::relationshipMatrix(Z,
              shape = shapes[shape], n_streams = streams[stream], tilesize = tiles[tile]
            )
          })[3]
        }
        tile_time[shape,tile,stream] <- tile_time[shape,tile,stream]/average_matrix
      }
    }
  }
}

# helper functions
my.min <- function(x) ifelse(!all(is.na(x)), min(x, na.rm=T), NA)
printf <- function(...) invisible(print(sprintf(...)))
# get best time
best <- which(tile_time == my.min(tile_time), arr.ind = TRUE)
print(my.min(tile_time))
printf("shape: %i tilesize: %i streams: %i", shapes[best[1]], tiles[best[2]], streams[best[3]])
rm(Z)
saveRDS(tile_time, "tile_time_old.rds")