A design reuse technology to increase productivity through automated corporate memory system

2016 ◽  
Vol 29 (9) ◽  
pp. 609-617 ◽  
Author(s):  
Murat Gunduz ◽  
Tamer Yetisir
Keyword(s):  
Memory System ◽  
Design Reuse ◽  
Corporate Memory ◽  
Increase Productivity

Finding and Understanding Reusable Designs from Large Hierarchical Repositories

2006 ◽  
Vol 5 (1) ◽  
pp. 28-46 ◽  
Author(s):  
Peter Demian ◽  
Renate Fruchter
Keyword(s):  
Engineering Design ◽  
Construction Projects ◽  
Civil Engineering ◽  
Usability Evaluation ◽  
Building Construction ◽  
Design Reuse ◽  
Link Diagram ◽  
Support Design ◽  
Corporate Memory

This paper describes a prototype called CoMem (Corporate Memory) that supports the finding and understanding of useful items in large hierarchical repositories. The particular domain is civil engineering design, and the prototype is designed specifically to support design reuse in building construction projects. However, the underlying visualization and interaction principals behind CoMem are generalizable to the ubiquitous task of finding and understanding useful information in large hierarchical repositories. To support the finding, the entire hierarchy is visualized using a squarified treemap. Once an item from the treemap is selected, CoMem supports the understanding of that item by identifying related items in the hierarchy and visualizing the selected item in the context of these related items in a node-link diagram. The paper concludes with a brief discussion of a usability evaluation of CoMem that supports the claim that finding and understanding improve the process of reuse, and that the described visualizations assist with finding and understanding.

scholarly journals GPU Domain Specialization via Composable On-Package Architecture

2022 ◽  
Vol 19 (1) ◽  
pp. 1-23
Author(s):  
Yaosheng Fu ◽  
Evgeny Bolotin ◽  
Niladrish Chatterjee ◽  
David Nellans ◽  
Stephen W. Keckler
Keyword(s):  
Deep Learning ◽  
Memory System ◽  
Design Reuse ◽  
Application Domain ◽  
Precision Matrix ◽  
Practical Solution ◽  
Optimal Configurations ◽  
Gpu Architecture ◽  
With Memory ◽  
Cache Capacity

As GPUs scale their low-precision matrix math throughput to boost deep learning (DL) performance, they upset the balance between math throughput and memory system capabilities. We demonstrate that a converged GPU design trying to address diverging architectural requirements between FP32 (or larger)-based HPC and FP16 (or smaller)-based DL workloads results in sub-optimal configurations for either of the application domains. We argue that a C omposable O n- PA ckage GPU (COPA-GPU) architecture to provide domain-specialized GPU products is the most practical solution to these diverging requirements. A COPA-GPU leverages multi-chip-module disaggregation to support maximal design reuse, along with memory system specialization per application domain. We show how a COPA-GPU enables DL-specialized products by modular augmentation of the baseline GPU architecture with up to 4× higher off-die bandwidth, 32× larger on-package cache, and 2.3× higher DRAM bandwidth and capacity, while conveniently supporting scaled-down HPC-oriented designs. This work explores the microarchitectural design necessary to enable composable GPUs and evaluates the benefits composability can provide to HPC, DL training, and DL inference. We show that when compared to a converged GPU design, a DL-optimized COPA-GPU featuring a combination of 16× larger cache capacity and 1.6× higher DRAM bandwidth scales per-GPU training and inference performance by 31% and 35%, respectively, and reduces the number of GPU instances by 50% in scale-out training scenarios.

What face familiarity feelings say about the lateralization of specific entities within the core system

2019 ◽  
Vol 42 ◽  
Author(s):  
Guido Gainotti
Keyword(s):  
Temporal Lobe ◽  
Memory System ◽  
Core System ◽  
The Core ◽  
Memory Traces ◽  
Specific Memory ◽  
Target Article ◽  
Temporal Structures ◽  
The Right

Abstract The target article carefully describes the memory system, centered on the temporal lobe that builds specific memory traces. It does not, however, mention the laterality effects that exist within this system. This commentary briefly surveys evidence showing that clear asymmetries exist within the temporal lobe structures subserving the core system and that the right temporal structures mainly underpin face familiarity feelings.

Study of effective factors in the design of zero energy buildings in arid climate (case of Isfahan City)

2018 ◽  
Vol 8 (1) ◽  
pp. 211-221
Author(s):  
Negar Aminoroayaei ◽  
Bahram Shahedi
Keyword(s):  
Fossil Fuels ◽  
Arid Climate ◽  
Zero Energy ◽  
Factors Affecting ◽  
Zero Energy Building ◽  
Cost Of Energy ◽  
Current Century ◽  
Increase Productivity ◽  
Save Energy ◽  
Zero Energy Buildings

In the current century, a suitable strategy is concerned for optimal consumption of energy, due to limited natural resources and fossil fuels for moving towards sustainable development and environmental protection. Given the rising cost of energy, environmental pollution and the end of fossil fuels, zero-energy buildings became a popular option in today's world. The purpose of this study is to investigate the factors affecting the design of zero-energy buildings, in order to reduce energy consumption and increase productivity, including plan form, climatic characteristics, materials, coverage etc. The present study collects the features of zero-energy building in Isfahan, which is based on the Emberger Climate View in the arid climate, by examining the books and related writings, field observations and using a descriptive method, in the form of qualitative studies. The results of the research showed that some actions are needed to save energy and, in general, less consumption of renewable energy by considering the climate and the use of natural conditions.

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