Portable data-parallel visualization and analysis in distributed memory environments

2013 ◽  
Author(s):  
Christopher Sewell ◽  
Li-ta Lo ◽  
James Ahrens
Keyword(s):  
Distributed Memory ◽  
Data Parallel ◽  
Parallel Visualization

MICROTHREADING A MODEL FOR DISTRIBUTED INSTRUCTION-LEVEL CONCURRENCY

2006 ◽  
Vol 16 (02) ◽  
pp. 209-228 ◽  
Author(s):  
CHRIS JESSHOPE
Keyword(s):  
Distributed Memory ◽  
Chip Multiprocessors ◽  
Dynamic Scheduling ◽  
Register File ◽  
Support Structures ◽  
Promising Candidate ◽  
Data Parallel ◽  
Fine Grain ◽  
Distributed Instruction

This paper analyses the micro-threaded model of concurrency making comparisons with both data and instruction-level concurrency. The model is fine grain and provides synchronisation in a distributed register file, making it a promising candidate for scalable chip-multiprocessors. The micro-threaded model was first proposed in 1996 as a means to tolerate high latencies in data-parallel, distributed-memory multi-processors. This paper explores the model's opportunity to provide the simultaneous issue of instructions, required for chip multiprocessors, and discusses the issues of scalability with regard to support structures implementing the model and communication in supporting it. The model supports deterministic distribution of code fragments and dynamic scheduling of instructions from within those fragments. The hardware also recognises different classes of variables from the register specifiers, which allows the hardware to manage locality and optimise communication so that it is both efficient and scalable.

Data Parallel and Scheduling Mechanism Based on Petri Nets

2014 ◽  
Vol 543-547 ◽  
pp. 3264-3267
Author(s):  
Wan Feng Dou ◽  
Jing Zhao ◽  
Kun Yang ◽  
Min Xu
Keyword(s):  
Parallel Computing ◽  
Petri Nets ◽  
Distributed Memory ◽  
Algorithm Design ◽  
Data Partition ◽  
Parallel Methods ◽  
Node Number ◽  
Data Parallel ◽  
Total Data ◽  
Data Granularity

Data-parallel and task-parallel methods are the basic methods frequently used for algorithm design in parallel computing. Data-parallel method as name means is used for partition data to be processed into some small blocks considering storage and computing capacity such as memory size of a computation node, node number to take part in parallel computing and total data size, and etc. On the other hand, data dispensing strategy is an important problem carefully considered to increase the efficiency of computation. According to the characteristics of analysis of digital terrain, petri nets is introduced to describe the parallel relationships within data partitions based on data granularity model considering two kinds of computing modes, shared memory and distributed memory respectively, and corresponding scheduling algorithms are proposed for load balance. The experimental results show that our method is very usable to data partition and dispensation, in particular to distributed memory mode.

scholarly journals Deployment and Analysis of a Hybrid Shared/Distributed-Memory Parallel Visualization Tool for 3-D Oil Reservoir Grid on OpenStack Cloud Computing

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 212280-212297
Author(s):  
Ali A. El-Moursy ◽  
Fadi N. Sibai ◽  
Hanan Khaled ◽  
Salwa M. Nassar ◽  
Mohamed Taher
Keyword(s):  
Cloud Computing ◽  
Distributed Memory ◽  
Oil Reservoir ◽  
Visualization Tool ◽  
Parallel Visualization

A Portable Implementation for Objective Caml Flight

2003 ◽  
Vol 13 (03) ◽  
pp. 425-436 ◽  
Author(s):  
EMMANUEL CHAILLOUX ◽  
CHRISTIAN FOISY
Keyword(s):  
Virtual Machine ◽  
Distributed Memory ◽  
Functional Language ◽  
Data Parallel ◽  
Current Implementation ◽  
New Distribution ◽  
Actual Realization ◽  
Do So ◽  
Parallel Extension

Caml-Flight is a data-parallel extension for Caml Light. It is an intermediate, portable and mostly deterministic functional language for distributed memory multiprocessors (DMM). Its current implementation modifies the Caml Light compiler to introduce new instructions for the language and its virtual machine, and to define a kind of persistence to communicate values. Caml Light has now evolved to become Objective Caml, including an object extension and a native compiler. To benefit from this new distribution, we propose a new implementation called Objective Caml Flight. To do so we use new libraries and tools included in Objective Caml such as multi-threading, persistence and parsers, i.e. without modification to the original compiler needed with the Caml-Flight approach. This paper presents an easier way to implement parallel extensions for Objective Caml and an actual realization called Objective Caml Flight. This new implementation is compared to Caml-Flight.

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