This document describes the process of acquiring and reproducing the experimental results presented in ``Performance Characterization of AutoNUMA Memory Tiering on Graph Analytics". This paper was accepted for publication at 2022 IEEE International Symposium on Workload Characterization (IISWC 2022)
This is the main deck presenting Performance-oriented Design of Scalable Graph Design. Key contents...
Hierarchical memory is a cornerstone of modern hardware design because it provides high memory perfo...
[[abstract]]Studies a representative of an important class of emerging applications: a parallel data...
Non-Volatile Memory (NVM) can deliver higher density and lower cost per bit when compared with DRAM....
Graph processing is experiencing a surge of renewed interest as applications in social networks and ...
Abstract. The characterization of workloads used in memory systems analysis and evaluation is import...
We process information in memory and different people have different memory capacity. It is therefor...
Big data, the large-scale collection and analysis of data, has become ubiquitous in the modern, digi...
© 2015 IEEE. Graph processing is an increasingly important application domain and is typically commu...
Abstract—Graph processing is an increasingly important ap-plication domain and is typically communic...
We identify several factors that are critical to high-performance GPU graph analytics: efficient bui...
Data-intensive applications have attracted considerable attention in recent years. Business organiza...
In modern computing environments, memory hierarchy expands from CPU registers, high speed caches, an...
Data center applications like graph analytics require servers with ever larger memory capacities. DR...
Graph-structured analytics has been widely adopted in a number of big data applications such as soci...
This is the main deck presenting Performance-oriented Design of Scalable Graph Design. Key contents...
Hierarchical memory is a cornerstone of modern hardware design because it provides high memory perfo...
[[abstract]]Studies a representative of an important class of emerging applications: a parallel data...
Non-Volatile Memory (NVM) can deliver higher density and lower cost per bit when compared with DRAM....
Graph processing is experiencing a surge of renewed interest as applications in social networks and ...
Abstract. The characterization of workloads used in memory systems analysis and evaluation is import...
We process information in memory and different people have different memory capacity. It is therefor...
Big data, the large-scale collection and analysis of data, has become ubiquitous in the modern, digi...
© 2015 IEEE. Graph processing is an increasingly important application domain and is typically commu...
Abstract—Graph processing is an increasingly important ap-plication domain and is typically communic...
We identify several factors that are critical to high-performance GPU graph analytics: efficient bui...
Data-intensive applications have attracted considerable attention in recent years. Business organiza...
In modern computing environments, memory hierarchy expands from CPU registers, high speed caches, an...
Data center applications like graph analytics require servers with ever larger memory capacities. DR...
Graph-structured analytics has been widely adopted in a number of big data applications such as soci...
This is the main deck presenting Performance-oriented Design of Scalable Graph Design. Key contents...
Hierarchical memory is a cornerstone of modern hardware design because it provides high memory perfo...
[[abstract]]Studies a representative of an important class of emerging applications: a parallel data...
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