11,609 research outputs found
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
Modular Acquisition and Stimulation System for Timestamp-Driven Neuroscience Experiments
Dedicated systems are fundamental for neuroscience experimental protocols
that require timing determinism and synchronous stimuli generation. We
developed a data acquisition and stimuli generator system for neuroscience
research, optimized for recording timestamps from up to 6 spiking neurons and
entirely specified in a high-level Hardware Description Language (HDL). Despite
the logic complexity penalty of synthesizing from such a language, it was
possible to implement our design in a low-cost small reconfigurable device.
Under a modular framework, we explored two different memory arbitration schemes
for our system, evaluating both their logic element usage and resilience to
input activity bursts. One of them was designed with a decoupled and latency
insensitive approach, allowing for easier code reuse, while the other adopted a
centralized scheme, constructed specifically for our application. The usage of
a high-level HDL allowed straightforward and stepwise code modifications to
transform one architecture into the other. The achieved modularity is very
useful for rapidly prototyping novel electronic instrumentation systems
tailored to scientific research.Comment: Preprint submitted to ARC 2015. Extended: 16 pages, 10 figures. The
final publication is available at link.springer.co
Design and implementation of a medium speed communications interface and protocol for a low cost, refreshed display computer
The design and implementation of hardware and software systems involved in using a 40,000 bit/second communication line as the connecting link between an IMLAC PDS 1-D display computer and a Univac 1108 computer system were described. The IMLAC consists of two independent processors sharing a common memory. The display processor generates the deflection and beam control currents as it interprets a program contained in the memory; the minicomputer has a general instruction set and is responsible for starting and stopping the display processor and for communicating with the outside world through the keyboard, teletype, light pen, and communication line. The processing time associated with each data byte was minimized by designing the input and output processes as finite state machines which automatically sequence from each state to the next. Several tests of the communication link and the IMLAC software were made using a special low capacity computer grade cable between the IMLAC and the Univac
Multilingual Language Processing From Bytes
We describe an LSTM-based model which we call Byte-to-Span (BTS) that reads
text as bytes and outputs span annotations of the form [start, length, label]
where start positions, lengths, and labels are separate entries in our
vocabulary. Because we operate directly on unicode bytes rather than
language-specific words or characters, we can analyze text in many languages
with a single model. Due to the small vocabulary size, these multilingual
models are very compact, but produce results similar to or better than the
state-of- the-art in Part-of-Speech tagging and Named Entity Recognition that
use only the provided training datasets (no external data sources). Our models
are learning "from scratch" in that they do not rely on any elements of the
standard pipeline in Natural Language Processing (including tokenization), and
thus can run in standalone fashion on raw text
- …