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There are a number of batch farms (i.e. collections of compute nodes) located in the central computing building and in the NEH and FEH experimental halls. Instructions describing how to submit jobs can be found on the Submitting Batch Job page.

The main batch farms farm currently consist of 80 nodes with the following general specifications:

• 12 cores, Xeon X5675, 24GB memory, QDR IB

and 40 nodes In addition, each experimental hall provides 20 nodes with access to the fast feedback storage layer (FFB). These nodes provide the resources for the high priority queues for the running experiments withand have the following specifications:

• 16 cores, Xeon E5-2640 v3, 128GB memory, QDR IB

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There are various ways to get real time information about the data acquired by an LCLS experiment. Users should be aware of the different possibilities and choose the approach that works best for their experiment. The methods for doing prompt analysis are described here.

Resources

The following diagram shows a logic diagram of the LCLS data flow and indicates the different stages where data analysis can be performed in LCLS: 

1. Online monitoring nodes - These nodes get the detector data over the network by snooping the multicast traffic between the DAQ readout nodes and the data cache layer. There is a set of monitoring nodes allocated for each instrument.
2. Fast feedback nodes - These nodes read the detector data from disk. By using the live option in psana, it's possible to read the data quasi real time as they are written to the FFB storage layer by the DAQ without the need to wait for the run to end. There is a farm of FFB nodes for each experimental hall.
3. Offline nodes - These nodes read the detector data from disk. These nodes, made of both interactive nodes (psana pool) and batch farms (psanaq queue), are main resource for doing data analysis and are shared across all LCLS instruments.