Abstract

Demonic memory is a form of reconstructive memory for process histories. As a process executes, its states are regularly checkpointed, generating a history of the process at low time resolution. Following the initial generation, any prior state of the process can be reconstructed by starting from a checkpointed state and re-executing the process up through the desired state, thereby exploiting the redundancy between the states of a process and the description of that process (i.e., a computer program). The reconstruction of states is automatic and transparent. The history of a process may be examined as though it were a large two-dimensional array, or address space-time , with a normal address space as one axis and steps of process time as the other. An attempt to examine a state that is not physically stored triggers a “demon” which reconstructs that memory state before access is allowed. Regeneration requires an exact description of the original execution of the process. If the original process execution depends on non-deterministic events (e.g., user input), these events are recorded in an exception list , and are replayed at the proper points during re-execution. While more efficient than explicitly storing all state changes, such a checkpointing system is still prohibitively expensive for many applications; each copy (or snapshot ) of the system's state may be very large, and many snapshots may be required. Demonic memory saves both space and time by using a virtual copy mechanism. (Virtual copies share unchanging data with the objects that they are copies of, only storing differences from a prototype or original [MiBK86].) In demonic memory, the snapshot at each checkpoint is a virtual copy of the preceding checkpoint's snapshot. Hence it is called a virtual snapshot . In order to make the virtual snapshot mechanism efficient, state information is initially saved in relatively large units of space and time, on the order of pages and seconds, with single-word/single-step regeneration undertaken only as needed. This permits the costs of indexing and lookup operations to be amortized over many locations.

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