[ANNOUNCE] KernelShark 2.0

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I am pleased to announce the new version of KernelShark has been released:

KernelShark 2.0



Major changes since 1.3:
- Introduces Data streams:
  With the help of Data stream, KernelShark is able to load and
  merge multiple trace files (streams). Each stream can have
  different plugins or filters, registered for it, which means that
  the raw trace data of the streams can have different formats, and
  will allow for a great degree of customization of the provided
  data visualization.

- New design of the plugin interface - instead of having a single
  interface for loading the plugin, we now have 3 different
  - The one that exists in version 1 of KernelShark is now renamed
    to Data Processing Interface (dpi).

  - The first new interface for loading can be used to register
    user provided implementation of the Data stream readout and is
    called Data Readout Interface (dri). Via this plugin loading
    interface the user can open trace data having an arbitrary
    format. In order to make this possible the user has to provide
    a plugin that contains an implementation of the data readout
    methods defined by the Data stream and to register all those

  - The second new plugin loading interface is called Control
    interface and can be used to provide the plugin with an access
    to the GUI's Main window object. Via this interface the plugin
    can became capable to modify the GUI.

- The modification of the C API are used to implement 3 new
  - KVMCombo plugin: The plugin allows the user to visualize
    the execution flow between the host and guest virtual machines.
    It exploits the concepts of "Data streams " and "Combo Plots"
    That allows to have two normal graphs from two data streams
    stacked together (on top of each other). The plugin uses a
    "combo" between the task in the host that emulates a virtual
    CPU and the corresponding CPU graph from the VM. The plugin
    draws additional graphical elements on top of this "combo",
    helping the user to intuitively interpret the data and see how
    the execution flow goes from host to guest and back.

  - LatencyPlot plugin: The plugin allows the user to visualize
    the latency between two events under the condition that the
    values of given data fields in the two events are identical
    (for example having the same PID). The plugin also registers
    its own dialog, that allows the user to select the events
    (and the matching field) to be visualized.

  - EventFieldPlot plugin: The plugin allows the user to visualize
    the recorded value of a given data field from a given trace
    event. The user can select the event and field to be visualized.


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