Design and implementation of a lossless parallel high-speed data compression system

2004 ◽  
Vol 15 (6) ◽  
pp. 481-490 ◽  
Author(s):  
M. Milward ◽  
J.L. Nunez ◽  
D. Mulvaney
Keyword(s):  
Data Compression ◽  
High Speed ◽  
Compression System ◽  
Design And Implementation ◽  
High Speed Data

scholarly journals Programming the Linpack Benchmark for the IBM PowerXCell 8i Processor

2009 ◽  
Vol 17 (1-2) ◽  
pp. 43-57 ◽  
Author(s):  
Michael Kistler ◽  
John Gunnels ◽  
Daniel Brokenshire ◽  
Brad Benton
Keyword(s):  
High Speed ◽  
Double Precision ◽  
Data Movement ◽  
Processing Elements ◽  
Cell Broadband Engine ◽  
Design And Implementation ◽  
Computational Capability ◽  
High Speed Data ◽  
Linpack Benchmark ◽  
And Performance

In this paper we present the design and implementation of the Linpack benchmark for the IBM BladeCenter QS22, which incorporates two IBM PowerXCell 8i1processors. The PowerXCell 8i is a new implementation of the Cell Broadband Engine™2 architecture and contains a set of special-purpose processing cores known as Synergistic Processing Elements (SPEs). The SPEs can be used as computational accelerators to augment the main PowerPC processor. The added computational capability of the SPEs results in a peak double precision floating point capability of 108.8 GFLOPS. We explain how we modified the standard open source implementation of Linpack to accelerate key computational kernels using the SPEs of the PowerXCell 8i processors. We describe in detail the implementation and performance of the computational kernels and also explain how we employed the SPEs for high-speed data movement and reformatting. The result of these modifications is a Linpack benchmark optimized for the IBM PowerXCell 8i processor that achieves 170.7 GFLOPS on a BladeCenter QS22 with 32 GB of DDR2 SDRAM memory. Our implementation of Linpack also supports clusters of QS22s, and was used to achieve a result of 11.1 TFLOPS on a cluster of 84 QS22 blades. We compare our results on a single BladeCenter QS22 with the base Linpack implementation without SPE acceleration to illustrate the benefits of our optimizations.

scholarly journals GIF IMAGE HARDWARE COMPRESSORS

2021 ◽  
Author(s):  
Ivan Mozghovyi ◽  
Anatoliy Sergiyenko ◽  
Roman Yershov
Keyword(s):  
Data Compression ◽  
Data Storage ◽  
High Speed ◽  
Data Transfer ◽  
Future Research ◽  
Volume Data ◽  
High Speed Data ◽  
Lzw Algorithm ◽  
And Storage ◽  
Speed Data Transmission

Increasing requirements for data transfer and storage is one of the crucial questions now. There are several ways of high-speed data transmission, but they meet limited requirements applied to their narrowly focused specific target. The data compression approach gives the solution to the problems of high-speed transfer and low-volume data storage. This paper is devoted to the compression of GIF images, using a modified LZW algorithm with a tree-based dictionary. It has led to a decrease in lookup time and an increase in the speed of data compression, and in turn, allows developing the method of constructing a hardware compression accelerator during the future research.

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