3,643 research outputs found
Energy Saving Techniques for Phase Change Memory (PCM)
In recent years, the energy consumption of computing systems has increased
and a large fraction of this energy is consumed in main memory. Towards this,
researchers have proposed use of non-volatile memory, such as phase change
memory (PCM), which has low read latency and power; and nearly zero leakage
power. However, the write latency and power of PCM are very high and this,
along with limited write endurance of PCM present significant challenges in
enabling wide-spread adoption of PCM. To address this, several
architecture-level techniques have been proposed. In this report, we review
several techniques to manage power consumption of PCM. We also classify these
techniques based on their characteristics to provide insights into them. The
aim of this work is encourage researchers to propose even better techniques for
improving energy efficiency of PCM based main memory.Comment: Survey, phase change RAM (PCRAM
Recommended from our members
Parallel data compression
Data compression schemes remove data redundancy in communicated and stored data and increase the effective capacities of communication and storage devices. Parallel algorithms and implementations for textual data compression are surveyed. Related concepts from parallel computation and information theory are briefly discussed. Static and dynamic methods for codeword construction and transmission on various models of parallel computation are described. Included are parallel methods which boost system speed by coding data concurrently, and approaches which employ multiple compression techniques to improve compression ratios. Theoretical and empirical comparisons are reported and areas for future research are suggested
Causal Consistency: Beyond Memory
In distributed systems where strong consistency is costly when not
impossible, causal consistency provides a valuable abstraction to represent
program executions as partial orders. In addition to the sequential program
order of each computing entity, causal order also contains the semantic links
between the events that affect the shared objects -- messages emission and
reception in a communication channel , reads and writes on a shared register.
Usual approaches based on semantic links are very difficult to adapt to other
data types such as queues or counters because they require a specific analysis
of causal dependencies for each data type. This paper presents a new approach
to define causal consistency for any abstract data type based on sequential
specifications. It explores, formalizes and studies the differences between
three variations of causal consistency and highlights them in the light of
PRAM, eventual consistency and sequential consistency: weak causal consistency,
that captures the notion of causality preservation when focusing on convergence
; causal convergence that mixes weak causal consistency and convergence; and
causal consistency, that coincides with causal memory when applied to shared
memory.Comment: 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel
Programming, Mar 2016, Barcelone, Spai
Parallel Batch-Dynamic Graph Connectivity
In this paper, we study batch parallel algorithms for the dynamic
connectivity problem, a fundamental problem that has received considerable
attention in the sequential setting. The most well known sequential algorithm
for dynamic connectivity is the elegant level-set algorithm of Holm, de
Lichtenberg and Thorup (HDT), which achieves amortized time per
edge insertion or deletion, and time per query. We
design a parallel batch-dynamic connectivity algorithm that is work-efficient
with respect to the HDT algorithm for small batch sizes, and is asymptotically
faster when the average batch size is sufficiently large. Given a sequence of
batched updates, where is the average batch size of all deletions, our
algorithm achieves expected amortized work per
edge insertion and deletion and depth w.h.p. Our algorithm
answers a batch of connectivity queries in expected
work and depth w.h.p. To the best of our knowledge, our algorithm
is the first parallel batch-dynamic algorithm for connectivity.Comment: This is the full version of the paper appearing in the ACM Symposium
on Parallelism in Algorithms and Architectures (SPAA), 201
- …