On Pronto, servers are dividedĀ into partitions based on intended use case.

To specify a partition when you submit your job, add this to your batch submission script:


Replace PARTITIONNAME with the name of the partition you want.

Choosing the correct partition when you submit your job will maximize its performance. If you do not specify a partition, your job will run on whatever server happens to be available.


interactive is intended for interactive terminal sessions.

Server Name CPU Cores RAM Features
biocrunch.las.iastate.edu 80 756 GB AVX
bigram.las.iastate.edu 48 1512 GB AVX


biocrunch is intended for jobs that do multithreaded computation.

Server Name CPU Cores RAM Features
biocrunch3.las.iastate.edu 176 1510 GB AVX512
biocrunch4.las.iastate.edu 176 1510 GB AVX512
biocrunch5.las.iastate.edu 176 1510 GB AVX512
biocrunch6.las.iastate.edu 176 1510 GB AVX512
biocrunch7.las.iastate.edu 176 1510 GB AVX512
biocrunch8.las.iastate.edu 176 1510 GB AVX512
biocrunch9.las.iastate.edu 192 1510 GB AVX512
biocrunch11.las.iastate.edu 192 1510 GB AVX512
biocrunch12.las.iastate.edu 192 1510 GB AVX512
biocrunch13.las.iastate.edu 192 1510 GB AVX512
biocrunch10.las.iastate.edu 192 1510 GB AVX512


speedy is intended for jobs that cannot be parallelized and require the fastest CPU.

Server Name CPU Cores RAM Features
speedy4.las.iastate.edu 32 376 GB AVX512
speedy5.las.iastate.edu 32 376 GB AVX512
speedy6.las.iastate.edu 32 376 GB AVX512
speedy7.las.iastate.edu 32 376 GB AVX512
speedy10.las.iastate.edu 32 376 GB AVX512
speedy11.las.iastate.edu 32 376 GB AVX512
speedy12.las.iastate.edu 32 376 GB AVX512
speedy.las.iastate.edu 24 252 GB AVX2
speedy2.las.iastate.edu 32 252 GB AVX2
speedy3.las.iastate.edu 32 377 GB AVX512
speedy8.las.iastate.edu 32 376 GB AVX512
speedy9.las.iastate.edu 32 376 GB AVX512


bigram is intended for jobs that cannot be parallelized and require a large amount of RAM, such as de novo genome assembly.

Server Name CPU Cores RAM Features
bigram2.las.iastate.edu 176 3022 GB AVX512


gpu is intended for jobs that need a gpu.

When submitting jobs to the gpu partition, you also need to add this to your batch script:

#SBATCH --partition=gpu
#SBATCH --gres=gpu:1

If you want a specific type of GPU, see the instructions under GPU types instead.


Server Name CPU Cores RAM GPUs Features
gpu03.las.iastate.edu 176 754 GB v100-pcie-16G x 2 AVX512
amp-5.las.iastate.edu 128 1008 GB a100-sxm4-80gb x 4 AVX2
amp-1.las.iastate.edu 64 504 GB a100-pcie x 4 AVX2
amp-2.las.iastate.edu 128 1008 GB a100-pcie x 8 AVX2
amp-3.las.iastate.edu 96 504 GB a100_2g.10gb x 12
a100_1g.5gb x 4
amp-4.las.iastate.edu 128 504 GB a100_3g.20gb x 2
a100-pcie x 3
crysis.las.iastate.edu 32 187 GB gtx_1080_ti x 8
v100-pcie-16G x 1
frost-1.las.iastate.edu 32 754 GB v100-sxm2-32G x 4 AVX512
frost-2.las.iastate.edu 32 376 GB rtx_2080_Ti x 4 AVX512
frost-3.las.iastate.edu 32 376 GB rtx_6000 x 4 AVX512
frost-4.las.iastate.edu 32 376 GB rtx_6000 x 4 AVX512
matrix.las.iastate.edu 96 376 GB v100-pcie-32G x 4 AVX512
singularity.las.iastate.edu 40 754 GB v100-sxm2-32G x 4 AVX512
frost-5.las.iastate.edu 32 376 GB rtx_6000 x 4 AVX512
frost-6.las.iastate.edu 32 376 GB rtx_6000 x 4 AVX512

GPU Types

To use a specific type of GPU, add this to your batch file:

#SBATCH --partition=gpu
#SBATCH --gres=gpu:GPUTYPE:1

Replace GPUTYPE with one of these types:

GPU Type RAM Compute Capability Quantity
a100_1g.5gb 5GB sm_80 4
a100_2g.10gb 10GB sm_80 12
a100_3g.20gb 20GB sm_80 2
a100-pcie 40GB sm_80 15
a100-sxm4-80gb 80GB sm_80 4
v100-pcie-16G 16GB sm_70 3
v100-pcie-32G 32GB sm_70 4
v100-sxm2-32G 32GB sm_70 8
rtx_2080_Ti 11GB sm_75 4
rtx_6000 24GB sm_75 16
gtx_1080_ti 11GB sm_61 8


The Legion servers are best for problems which can be highly parallelized (particularly where each thread is doing something slightly different from the others).

Each legion node has a very large number of cores available, but those cores are slower than those found on a typical Intel Xeon processor like you'll find on our other servers.

Due to the large number of cores, these servers are faster at processing particular types of workloads such as molecular dynamics, genome alignment, and monte carlo simulations.

Server Name CPU Cores RAM Features
legion-1.las.iastate.edu 272 378 GB AVX512
legion-2.las.iastate.edu 272 378 GB AVX512
legion-3.las.iastate.edu 272 378 GB AVX512
legion-4.las.iastate.edu 272 378 GB AVX512
legion-5.las.iastate.edu 272 378 GB AVX512
legion-6.las.iastate.edu 272 378 GB AVX512
legion-7.las.iastate.edu 272 378 GB AVX512
legion-8.las.iastate.edu 272 378 GB AVX512


A hybrid between biocrunch and speedy. Faster core speed, and more of them. With better IPC and memory bandwidth.

Server Name CPU Cores RAM Features
swift-5.las.iastate.edu 64 504 GB AVX2
swift-6.las.iastate.edu 64 504 GB AVX2
swift-7.las.iastate.edu 64 504 GB AVX2
swift-8.las.iastate.edu 64 504 GB AVX2
swift-9.las.iastate.edu 64 504 GB AVX2
swift-10.las.iastate.edu 64 504 GB AVX2
swift-11.las.iastate.edu 64 504 GB AVX2
swift-12.las.iastate.edu 64 504 GB AVX2