Results 221 to 230 of about 583,369 (247)

Enabling near-data processing in distributed object storage systems

Proceedings of the 13th ACM Workshop on Hot Topics in Storage and File Systems, 2021
Most general-purpose distributed storage systems are not designed with near data processing (NDP) in mind. They do not respect semantic data boundaries when writing data, for example splitting a record across servers. This reduces NDP effectiveness by requiring data collation before computation.
Ian F. Adams, Neha Agrawal, Michael P. Mesnier   +2 more
openaire   +1 more source

An architecture for near-data processing systems

Proceedings of the ACM International Conference on Computing Frontiers, 2016
Near-data processing is a promising paradigm to address the bandwidth, latency, and energy limitations in today's computer systems. In this work, we introduce an architecture that enhances a contemporary multi-core CPU with new features for supporting a seamless integration of near-data processing capabilities.
Erik Vermij, Christoph Hagleitner, Leandro Fiorin, Rik Jongerius, Jan van Lunteren, Koen Bertels   +5 more
openaire   +1 more source

GCiM: A Near-Data Processing Accelerator for Graph Construction

2021 58th ACM/IEEE Design Automation Conference (DAC), 2021
Graph is widely utilized as a key data structure in many applications like social network and recommendation systems. However, real-world graph construction typically involves massive random memory accesses and distance calculation, resulting in considerable processing time and energy consumptions on CPUs and GPUs.
Lei He, Cheng Liu, Ying Wang, Shengwen Liang, Huawei Li, Xiaowei Li   +5 more
openaire   +1 more source

Towards Near Data Processing of Convolutional Neural Networks

2018 31st International Conference on VLSI Design and 2018 17th International Conference on Embedded Systems (VLSID), 2018
The gap between the processing speed of the CPU and the access speed of the memory is becoming a bottleneck for many data intensive applications. This gap can be reduced if the computation can be taken near to the data. Recent advancement in memory technology has made it feasible to have 3D stacked memory along with the capability of having an ...
Palash Das, Shivam Lakhotia, Prabodh Shetty, Hemangee K. Kapoor   +3 more
openaire   +1 more source

Accelerating Linked-list Traversal Through Near-Data Processing

Proceedings of the 2016 International Conference on Parallel Architectures and Compilation, 2016
Recent technology advances in memory system design, along with 3D stacking, have made near-data processing (NDP) more feasible to accelerate different workloads. In this work, we explore the near-data processing opportunity of a fundamental operation - linked-list traversal (LLT).
Byungchul Hong, Gwangsun Kim, Jung Ho Ahn, Yongkee Kwon, Hongsik Kim, John Kim   +5 more
openaire   +1 more source

Near-Data-Processing for Data-Intensive Applications

2023
The information technology sector has experienced explosive growth in data-intensive applications such as bioinformatics, big data analytics, and deep neural networks (DNNs). These computing tasks have a tremendous economic impact and societal benefits, but their execution on conventional Von Neumann architectures is inefficient due to excessive data ...
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GNP: A Global-Sensitive Mechanism for Near-Data Processing

2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS), 2020
With the information processing technology changing from “computation-intensive” to “data-intensive”, “Memory wall” is becoming a problem which cannot be ignored. Near-data processing (NDP) architecture becomes an effective means to improve the performance of the system and reduce the energy consumption.
Xianfeng Li, Juanjuan Zhao
openaire   +1 more source

Sorting big data on heterogeneous near-data processing systems

Proceedings of the Computing Frontiers Conference, 2017
Big data workloads assumed recently a relevant importance in many business and scientific applications. Sorting elements efficiently in big data workloads is a key operation. In this work, we analyze the implementation of the mergesort algorithm on heterogeneous systems composed of CPUs and near-data processors located on the system memory channels ...
Erik Vermij, Leandro Fiorin, Christoph Hagleitner, Koen Bertels   +3 more
openaire   +1 more source

Leveraging near data processing for high-performance checkpoint/restart

Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2017
With the increasing size of HPC systems, the system mean time to interrupt will decrease. This requires checkpoints to be stored in a smaller time when using checkpoint/restart (C/R) for mitigation. Multilevel checkpointing improves C/R efficiency by saving most checkpoints to fast compute-node local storage. But it incurs a high cost for writing a few
Abhinav Agrawal, Gabriel H. Loh, James Tuck   +2 more
openaire   +1 more source

Near-Data Processing: Insights from a MICRO-46 Workshop

IEEE Micro, 2014
The cost of data movement in big-data systems motivates careful examination of near-data processing (NDP) frameworks. The concept of NDP was actively researched in the 1990s, but gained little commercial traction. After a decade-long dormancy, interest in this topic has spiked. A workshop on NDP was organized at MICRO-46 and was well attended.
Rajeev Balasubramonian, Jichuan Chang, Troy Manning, Jaime H. Moreno, Richard Murphy, Ravi Nair, Steven Swanson   +6 more
openaire   +1 more source