Hardware requirements¶
MetAMOS was designed to work on any standard 64bit Linux or OSX environment. To use MetAMOS for tutorial/teaching purposes, a minimum of 16 GB RAM is recommended. To get started on real data sets a minimum of 64 GB of RAM is recommended, and up to 1 TB of RAM may be necessary for larger datasets. In our experience, for most 50-100 million read datasets, 64-128 GB is a good place to start.
Scenario #1: running locally on large memory server¶
Suggested all-purpose build:
- 256 GB RAM (16 x 16GB)
- 48 cores (96 HT, 4x cpu)
- 1 TB SSD temporary scratch space for running analyses
- 16 TB HDD archival space for storing analyses
Scenario #2: running on local cluster/grid¶
Notes:
- Great for BLAST intense jobs
- RAM will limit the supported assemblers
- Grid job submission via SGE, others not supported
- MPI install required for Ray Meta
Scenario #3: running on cloud via Amazon EC2 High Memory¶
Recommend for best price/performance ratio -> cr1.8xlarge (Memory optimized):
- 2 X 120 GB SSD
- 32 HT x 2.8GhZ
- 244 GB RAM
- Spot instance currently at $0.361 per Hour (based on availability)
- On demand instance at $3.500 per Hour (always available)
- Reserved instance at $1.54 per Hour, $2474 upfront, approx. $2000 a month
More info on spot instances: http://aws.amazon.com/ec2/purchasing-options/spot-instances/
Or for smaller assembly jobs -> c3.8xlarge (Compute optimized):
- 2 X 320 GB SSD
- 32 HT x 2.8GhZ
- 60 GB RAM
- On demand instance at $2.400 per Hour (spot instance same price!)
Here is a very useful cost calculator: https://www.scalyr.com/cloud/
Don’t forget to account for time/cost to upload data!