33,443 research outputs found
Trajectory Codes for Flash Memory
Flash memory is well-known for its inherent asymmetry: the flash-cell charge
levels are easy to increase but are hard to decrease. In a general rewriting
model, the stored data changes its value with certain patterns. The patterns of
data updates are determined by the data structure and the application, and are
independent of the constraints imposed by the storage medium. Thus, an
appropriate coding scheme is needed so that the data changes can be updated and
stored efficiently under the storage-medium's constraints.
In this paper, we define the general rewriting problem using a graph model.
It extends many known rewriting models such as floating codes, WOM codes,
buffer codes, etc. We present a new rewriting scheme for flash memories, called
the trajectory code, for rewriting the stored data as many times as possible
without block erasures. We prove that the trajectory code is asymptotically
optimal in a wide range of scenarios.
We also present randomized rewriting codes optimized for expected performance
(given arbitrary rewriting sequences). Our rewriting codes are shown to be
asymptotically optimal.Comment: Submitted to IEEE Trans. on Inform. Theor
[Report of] Specialist Committee V.4: ocean, wind and wave energy utilization
The committee's mandate was :Concern for structural design of ocean energy utilization devices, such as offshore wind turbines, support structures and fixed or floating wave and tidal energy converters. Attention shall be given to the interaction between the load and the structural response and shall include due consideration of the stochastic nature of the waves, current and wind
Rewriting Codes for Joint Information Storage in Flash Memories
Memories whose storage cells transit irreversibly between
states have been common since the start of the data storage
technology. In recent years, flash memories have become a very
important family of such memories. A flash memory cell has q
states—state 0.1.....q-1 - and can only transit from a lower
state to a higher state before the expensive erasure operation takes
place. We study rewriting codes that enable the data stored in a
group of cells to be rewritten by only shifting the cells to higher
states. Since the considered state transitions are irreversible, the
number of rewrites is bounded. Our objective is to maximize the
number of times the data can be rewritten. We focus on the joint
storage of data in flash memories, and study two rewriting codes
for two different scenarios. The first code, called floating code, is for
the joint storage of multiple variables, where every rewrite changes
one variable. The second code, called buffer code, is for remembering
the most recent data in a data stream. Many of the codes
presented here are either optimal or asymptotically optimal. We
also present bounds to the performance of general codes. The results
show that rewriting codes can integrate a flash memory’s
rewriting capabilities for different variables to a high degree
Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS
GROMACS is a widely used package for biomolecular simulation, and over the
last two decades it has evolved from small-scale efficiency to advanced
heterogeneous acceleration and multi-level parallelism targeting some of the
largest supercomputers in the world. Here, we describe some of the ways we have
been able to realize this through the use of parallelization on all levels,
combined with a constant focus on absolute performance. Release 4.6 of GROMACS
uses SIMD acceleration on a wide range of architectures, GPU offloading
acceleration, and both OpenMP and MPI parallelism within and between nodes,
respectively. The recent work on acceleration made it necessary to revisit the
fundamental algorithms of molecular simulation, including the concept of
neighborsearching, and we discuss the present and future challenges we see for
exascale simulation - in particular a very fine-grained task parallelism. We
also discuss the software management, code peer review and continuous
integration testing required for a project of this complexity.Comment: EASC 2014 conference proceedin
Cost-Effective Clustering
Small Beowulf clusters can effectively serve as personal or group
supercomputers. In such an environment, a cluster can be optimally designed for
a specific problem (or a small set of codes). We discuss how theoretical
analysis of the code and benchmarking on similar hardware lead to optimal
systems.Comment: 7 pages, 2 figures (one in color). Color version of paper to be
published as part of proceedings of CCP2000 (Brisbane) in a special isssue of
Computer Physics Communication
Performance of an Echo Canceller and Channel Estimator for On-Channel Repeaters in DVB-T/H Networks
This paper investigates the design and performance of an FIR echo canceller for on-channel repeaters in DVB-T/H network within the framework of the PLUTO project. The possible
approaches for echo cancellation are briefly reviewed and the main guidelines for the design of such systems are presented. The main system parameters are discussed. The performance of an FIR echo canceller based on an open loop feedforward approach for channel estimation is tested for different radio channel conditions and for different number of taps of the FIR filter. It is shown that a minimum number of taps is recommended to achieve a certain mean rejection ratio or isolation depending on the type of channel. The expected degradation in performance due to the use of fixed point rather than floating point arithmetic in hardware implementation is presented for different number of bits. Channel estimation based on training sequences is investigated. The performance of Maximum Length Sequences and Constant Amplitude Zero Autocorrelation (CAZAC) Sequences is compared for different channels. Recommendations are given for training sequence type, length and
level for DVB-T/H on-channel repeater deployment
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