Abstract-An efficient multiversion access structure for a transaction-time database is presented. Our method requires optimal storage and query times for several important queries and logarithmic update times. Three version operations}inserts, updates, and deletes}are allowed on the current database, while queries are allowed on any version, present or past. The following query operations are performed in optimal query time: key range search, key history search, and time range view. The key-range query retrieves all records having keys in a specified key range at a specified time; the key history query retrieves all records with a given key in a specified time range; and the time range view query retrieves all records that were current during a specified time interval. Special cases of these queries include the key search query, which retrieves a particular version of a record, and the snapshot query which reconstructs the database at some past time. To the best of our knowledge no previous multiversion access structure simultaneously supports all these query and version operations within these time and space bounds. The bounds on query operations are worst case per operation, while those for storage space and version operations are (worst-case) amortized over a sequence of version operations. Simulation results show that good storage utilization and query performance is obtained.
We provide a competitive analysis framework for online prefetching and buffer management algorithms in parallel IrO systems, using a read-once model of block references. This has widespread applicability to key IrO-bound applications such as external merging and concurrent playback of multiple video streams. Two realistic lookahead models, global lookahead and local lookahead, are defined. Algorithms NOM and GREED, based on these two forms of lookahead are analyzed for shared buffer and distributed buffer configurations, both of which COMPETITIVE PARALLEL DISK PREFETCHING 153 occur frequently in existing systems. An important aspect of our work is that we show how to implement both of the models of lookahead in practice using the simple techniques of forecasting and flushing.Given a D-disk parallel IrO system and a globally shared IrO buffer that can ' Ž . hold up to M disk blocks, we derive a lower bound of ⍀ D on the competitive Ž . ratio of any deterministic online prefetching algorithm with O M lookahead. NOM is shown to match the lower bound using global M-block lookahead. In Ž . contrast, using only local lookahead results in an ⍀ D competitive ratio. When the buffer is distributed into D portions of MrD blocks each, the algorithm GREED based on local lookahead is shown to be optimal, and NOM is within a constant factor of optimal. Thus we provide a theoretical basis for the intuition that global lookahead is more valuable for prefetching in the case of a shared buffer configuration, whereas it is enough to provide local lookahead in the case of a distributed configuration. Finally, we analyze the performance of these algorithms for reference strings generated by a uniformly-random stochastic process and we show that they achieve the minimal expected number of IrOs. These results also give bounds on the worst-case expected performance of algorithms which employ randomization in the data layout. ᮊ
Advances in memory technology are promising the availability of byte-addressable persistent memory as an integral component of future computing platforms. This change has significant implications for software that has traditionally made a sharp distinction between durable and volatile storage. In this paper we describe a softwarehardware architecture, WrAP, for persistent memory that provides atomicity and durability while simultaneously ensuring that fast paths through the cache, DRAM, and persistent memory layers are not slowed down by burdensome buffering or double-copying requirements. Trace-driven simulation of transactional data structures indicate the potential for significant performance gains using the WrAP approach.
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