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Buffering Target

Gerd Heber edited this page Jul 21, 2021 · 11 revisions

A buffering target represents a logical target of data placement, i.e., parts of or a full blob can be placed there by the DPE. Buffering targets are logical constructs that are statically mapped by Hermes to underlying physical resources.

Terminology

A buffering target consists of two components:

Virtual Device

This represents a way to get to the actual storage. It could be a file handle and an offset, a memory address, a partition of a drive, etc.

NodeID

The identifier of the node that is responsible for the virtual device.

Tiers are the partitions of a partitioned set of targets order by a score, which is calculated based on a set of prioritized characteristics. Tier 1 represents the "best" targets according to the prioritized characteristics, and the tiers get "worse" as the tier number increases. For example, tier 1 might be a local RAM target when bandwidth is the ordering characteristic, but it might be a burst buffer target when remaining capacity is prioritized.

When the DPE runs, it is given an appropriate list of targets. If a placement fails, it can request an extended list of targets (neighborhood or global).

For now we map 1 TargetID to 1 (NodeID, VirtualDevice) pair, but the option is open for 1 to n and n to m.


The set of targets can be partitioned in the form of topologies. In some cases, the aggregate characteristics of such partitions can be defined based on the characteristics of the underlying targets.


Goals

  • Provide a way for the DPE to operate on a reduced (or custom) set of resources.
  • Remove certain resources from DPE consideration.
  • Create orderings of resources based on characteristics (i.e., tiered groups).

Charateristics

Each buffering target has the following characteristics.

  • Targets (d_i, i=1,\ldots,D)
    • Target configuration/specs.
      • (Cap[d_i]) - the total capacity of target (d_i)
      • (Wbw[d_i]) - the HW max. write bandwidth of target (d_i)
      • (Rbw[d_i]) - the HW max. read bandwidth of target (d_i)
      • (Alat[d_i]) - the average HW access latency of target (d_i) (measured as time)
      • (Pwr[d_i]) - the energy consumption of target (d_i) (measured in Watts)
      • (Concy[d_i]) - the HW concurrency of target (d_i) (measured in lane count)
      • (End[d_i]) - the endurance (wear and tear) of target (d_i) (measured as percentage of the expected storage cycles over the life time)
      • (Rrat[d_i]) - the reliability rating of target (d_i) (measured in Trumps)
      • (Speed[d_i]) - the average I/O speed of target (d_i) (measured as MB/s)
    • Variables
      • (Avail[d_i]) - the availability of target (d_i) (Boolean)
      • (Rem[d_i]) - the remaining capacity of target (d_i)
      • (Load[d_i]) - the expected completion time of outstanding requests on target

Example

Assume a system with 3 nodes, each with three targets (RAM, NVMe, and burst buffer). Assume a neighborhood is any 2 of the three nodes. This means a local target list will consist of 3 targets, a neighborhood of 6, and the global target list of 9.

Kitchen Sink

From the OctopusFS paper:

  • Tiers T1, …, Tk
  • Media mi
    • Tier[mi] - the tier of medium mi
    • Cap[mi] - the total capacity of medium mi
    • Rem[mi] - the remaining capacity of medium mi
    • NrConn[mi] - the number of active I/O connections to medium mi
    • WThru[mi] - the sustained write throughput of medium mi
    • RThru[mi] - the sustained read throughput of medium mi
  • Workers W1, …, Wn
    • Slightly different concept
      • Stores and manages file blocks on storage media
      • Serves read and write requests from clients
      • Block creation, deletion, replication (instructed by name nodes HDFS...)

From Wrike:

  • Wi =  < node, tier>
  • Workers are a dedicated thread per tier available on the node
  • Worker characteristics:
    • Capacity
    • BW
    • Latency
    • Energy consumption
    • Concurrency (expressed as the number of lanes of the bus e.g., PCIex8 or SATA)
    • Queue pressure (outstanding requests)
      • Aggregate data size in queue
      • Number of pending requests
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