2,323 research outputs found
Improving the Performance and Endurance of Persistent Memory with Loose-Ordering Consistency
Persistent memory provides high-performance data persistence at main memory.
Memory writes need to be performed in strict order to satisfy storage
consistency requirements and enable correct recovery from system crashes.
Unfortunately, adhering to such a strict order significantly degrades system
performance and persistent memory endurance. This paper introduces a new
mechanism, Loose-Ordering Consistency (LOC), that satisfies the ordering
requirements at significantly lower performance and endurance loss. LOC
consists of two key techniques. First, Eager Commit eliminates the need to
perform a persistent commit record write within a transaction. We do so by
ensuring that we can determine the status of all committed transactions during
recovery by storing necessary metadata information statically with blocks of
data written to memory. Second, Speculative Persistence relaxes the write
ordering between transactions by allowing writes to be speculatively written to
persistent memory. A speculative write is made visible to software only after
its associated transaction commits. To enable this, our mechanism supports the
tracking of committed transaction ID and multi-versioning in the CPU cache. Our
evaluations show that LOC reduces the average performance overhead of memory
persistence from 66.9% to 34.9% and the memory write traffic overhead from
17.1% to 3.4% on a variety of workloads.Comment: This paper has been accepted by IEEE Transactions on Parallel and
Distributed System
A distributed file service based on optimistic concurrency control
The design of a layered file service for the Amoeba Distributed System is discussed, on top of which various applications can easily be intplemented. The bottom layer is formed by the Amoeba Block Services, responsible for implementing stable storage and repficated, highly available disk blocks. The next layer is formed by the Amoeba File Service which provides version management and concurrency control for tree-structured files. On top of this layer, the appficafions, ranging from databases to source code control systems, determine the structure of the file trees and provide an interface to the users
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Improving DBMS performance through diverse redundancy
Database replication is widely used to improve both fault tolerance and DBMS performance. Non-diverse database replication has a significant limitation - it is effective against crash failures only. Diverse redundancy is an effective mechanism of tolerating a wider range of failures, including many non-crash failures. However it has not been adopted in practice because many see DBMS performance as the main concern. In this paper we show experimental evidence that diverse redundancy (diverse replication) can bring benefits in terms of DBMS performance, too. We report on experimental results with an optimistic architecture built with two diverse DBMSs under a load derived from TPC-C benchmark, which show that a diverse pair performs faster not only than non-diverse pairs but also than the individual copies of the DBMSs used. This result is important because it shows potential for DBMS performance better than anything achievable with the available off-the-shelf servers
Fine-Grain Checkpointing with In-Cache-Line Logging
Non-Volatile Memory offers the possibility of implementing high-performance,
durable data structures. However, achieving performance comparable to
well-designed data structures in non-persistent (transient) memory is
difficult, primarily because of the cost of ensuring the order in which memory
writes reach NVM. Often, this requires flushing data to NVM and waiting a full
memory round-trip time.
In this paper, we introduce two new techniques: Fine-Grained Checkpointing,
which ensures a consistent, quickly recoverable data structure in NVM after a
system failure, and In-Cache-Line Logging, an undo-logging technique that
enables recovery of earlier state without requiring cache-line flushes in the
normal case. We implemented these techniques in the Masstree data structure,
making it persistent and demonstrating the ease of applying them to a highly
optimized system and their low (5.9-15.4\%) runtime overhead cost.Comment: In 2019 Architectural Support for Programming Languages and Operating
Systems (ASPLOS 19), April 13, 2019, Providence, RI, US
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