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Concurrent vs. Exclusive Reading in Parallel Decoding of LZ-Compressed Files^{ †}

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## Abstract

**:**

## 1. Introduction

## 2. Concurrent versus Exclusive Reading

## 3. Decoding LZC-Compressed Files in Parallel

#### 3.1. LZC Compression

#### 3.2. The CREW PRAM Algorithm

input: sequence of pointers q_{1}...q_{m}; output: matrix M of prefix pointers; 1. k := 1; 2.in parallel for1 ≤ i ≤ mdo3. M[i, j] := q_{i}; 4. last[i] := 1; 5. value[i] := M[i, j] − d; 6.whilevalue[i] > 0do7.in parallel for1 ≤ j ≤ kdo8.ifj ≤ last[value[i]]then9. M[last[i] + j.i] = M[j, value[i]; 10. last[i] := last[i] + last[value[i]]; 11. value[i] := value[value[i]]; 13. k := 2k;

#### 3.3. The EREW PRAM Algorithm

## 4. The MapReduce Implementation of the CREW Algorithm

#### 4.1. The MapReduce Model of Computation

- R is polylogarithmic in the input size n;
- the number of processors (or nodes in the Web) involved is O(${n}^{1-\u03f5}$) with $0<\u03f5<1$;
- the amount of memory for each node is O(${n}^{1-\u03f5}$);
- mappers and reducers take polynomial time in n.

#### 4.2. Decoding LZC-Compressed Files in MapReduce

#### 4.3. Complexity Issues

## 5. Conclusions

## Author Contributions

## Conflicts of Interest

## References

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**MDPI and ACS Style**

Agostino, S.D.; Carpentieri, B.; Pizzolante, R.
Concurrent vs. Exclusive Reading in Parallel Decoding of LZ-Compressed Files. *Algorithms* **2017**, *10*, 21.
https://doi.org/10.3390/a10010021

**AMA Style**

Agostino SD, Carpentieri B, Pizzolante R.
Concurrent vs. Exclusive Reading in Parallel Decoding of LZ-Compressed Files. *Algorithms*. 2017; 10(1):21.
https://doi.org/10.3390/a10010021

**Chicago/Turabian Style**

Agostino, Sergio De, Bruno Carpentieri, and Raffaele Pizzolante.
2017. "Concurrent vs. Exclusive Reading in Parallel Decoding of LZ-Compressed Files" *Algorithms* 10, no. 1: 21.
https://doi.org/10.3390/a10010021