scholarly journals Special issue on trends in high-performance interconnection networks in the exascale and big-data era

2017 ◽  
Vol 29 (13) ◽  
pp. e4176
Author(s):  
Jesús Escudero-Sahuquillo ◽  
Pedro Javier Garcia
Keyword(s):  
Big Data ◽  
Interconnection Networks ◽  
High Performance ◽  
Special Issue

scholarly journals Special Issue on Programming Languages for Big Data Editorial

2018 ◽  
Vol 28 ◽  
Author(s):  
James Cheney ◽  
Torsten Grust
Keyword(s):  
Big Data ◽  
Programming Languages ◽  
High Performance ◽  
Database System ◽  
Research Area ◽  
Distributed Programming ◽  
Special Issue ◽  
Creative Research ◽  
Database Programming Languages ◽  
Advanced Applications

Ideas from programming languages play an important role in a range of advanced applications of databases, in database system implementation, distributed programming (MapReduce), streaming computation, and high-performance (GPU/multicore) computation. This creative research area is broadening into a subfield of data-centric computation. Although the interaction of databases and programming has a long history (the 16th biennial Database Programming Languages symposium was held in 2017), there has been a recent renewal of interest and broadening of programming language techniques for dealing with data from several quarters in the last few years, including workshops at Microsoft Research (RADICAL 2010), ICFP (XLDI 2012), POPL (DDFP 2013, DCM 2014) and a Dagstuhl Seminar on Programming Languages for Big Data (December 2014). This special issue recognises and encourages the publication of mature research contributions in this area.

scholarly journals High-performance interconnection networks in the Exascale and Big-Data Era

2016 ◽  
Vol 72 (12) ◽  
pp. 4415-4417 ◽  
Author(s):  
Jesús Escudero-Sahuquillo ◽  
Pedro Javier Garcia
Keyword(s):  
Big Data ◽  
Interconnection Networks ◽  
High Performance

Efficient Instruction and Data Caching for High Performance Embedded Processors

1970 ◽  
pp. 9
Author(s):  
A. Ferrerón Labari ◽  
D. Suárez Gracia ◽  
V. Viñals Yúfera
Keyword(s):  
Embedded Systems ◽  
Power Consumption ◽  
Low Power ◽  
Interconnection Networks ◽  
High Performance ◽  
Critical Issue ◽  
Content Management ◽  
Structure Design ◽  
Portable Devices ◽  
On Chip

In the last years, embedded systems have evolved so that they offer capabilities we could only find before in high performance systems. Portable devices already have multiprocessors on-chip (such as PowerPC 476FP or ARM Cortex A9 MP), usually multi-threaded, and a powerful multi-level cache memory hierarchy on-chip. As most of these systems are battery-powered, the power consumption becomes a critical issue. Achieving high performance and low power consumption is a high complexity challenge where some proposals have been already made. Suarez et al. proposed a new cache hierarchy on-chip, the LP-NUCA (Low Power NUCA), which is able to reduce the access latency taking advantage of NUCA (Non-Uniform Cache Architectures) properties. The key points are decoupling the functionality, and utilizing three specialized networks on-chip. This structure has been proved to be efficient for data hierarchies, achieving a good performance and reducing the energy consumption. On the other hand, instruction caches have different requirements and characteristics than data caches, contradicting the low-power embedded systems requirements, especially in SMT (simultaneous multi-threading) environments. We want to study the benefits of utilizing small tiled caches for the instruction hierarchy, so we propose a new design, ID-LP-NUCAs. Thus, we need to re-evaluate completely our previous design in terms of structure design, interconnection networks (including topologies, flow control and routing), content management (with special interest in hardware/software content allocation policies), and structure sharing. In CMP environments (chip multiprocessors) with parallel workloads, coherence plays an important role, and must be taken into consideration.

Guest Editorial: Special Issue on Big Data

2020 ◽  
pp. -1--1
Author(s):  
Arun Sangaiah ◽  
Ford Gao ◽  
Krishn Mishra
Keyword(s):  
Big Data ◽  
Guest Editorial ◽  
Special Issue ◽  
Editorial Special Issue

Call for Special Issue Papers: Multimedia Big Data Analytics for Engineering Education

Big Data ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 87-88
Author(s):  
Priyan Malarvizhi Kumar ◽  
Hari Mohan Pandey ◽  
Gautam Srivastava
Keyword(s):  
Big Data ◽  
Engineering Education ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Special Issue ◽  
Multimedia Big Data
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