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Fast Lossless Compression of Scientific Floating-Point Data
In scientific computing environments, large amounts of floating-point data often need to
be transferred between computers as well as to and from storage devices. Compression
can reduce the number of bits that need to be transferred and stored. However, the runtime
overhead due to compression may be undesirable in high-performance settings
where short communication latencies and high bandwidths are essential. This paper describes
and evaluates a new compression algorithm that is tailored to such environments.
It typically compresses numeric floating-point values better and faster than other algorithms
do. On our data sets, it achieves compression ratios between 1.2 and 4.2 as well
as compression and decompression throughputs between 2.8 and 5.9 million 64-bit double-precision
numbers per second on a 3GHz Pentium 4 machine
paper  comp-sci  compression  algorithms  data  filetype:pdf 
april 2017 by jabley
High Throughput Compression of Double-Precision Floating-Point Data
This paper describes FPC, a lossless compression algorithm for linear streams of 64-bit
floating-point data. FPC is designed to compress well while at the same time meeting the
high throughput demands of scientific computing environments. On our thirteen datasets,
it achieves a substantially higher average compression ratio than BZIP2, DFCM, FSD,
GZIP, and PLMI. At comparable compression ratios, it compresses and decompresses 8
to 300 times faster than the other five algorithms.
paper  comp-sci  compression  algorithms  data  filetype:pdf 
april 2017 by jabley
HyParView: a membership protocol for reliable gossip-based broadcast
Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly
scalable and resilient reliable broadcast primitives. Due to scalability reasons, each participant
in a gossip protocol maintains a partial view of the system. The reliability of the gossip
protocol depends upon some critical properties of these views, such as degree distribution and
clustering coefficient.
Several algorithms have been proposed to maintain partial views for gossip protocols. In
this paper, we show that under a high number of faults, these algorithms take a long time to
restore the desirable view properties. To address this problem, we present HyParView, a new
membership protocol to support gossip-based broadcast that ensures high levels of reliability
even in the presence of high rates of node failure. The HyParView protocol is based on a
novel approach that relies in the use of two distinct partial views, which are maintained with
different goals by different strategies.
distributed-systems  algorithms  engineering  gossip  paper  filetype:pdf 
november 2016 by jabley
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