Works (7)

Updated: July 5th, 2023 15:37

2019 article

Dynamic Multi-Resolution Data Storage

MICRO'52: THE 52ND ANNUAL IEEE/ACM INTERNATIONAL SYMPOSIUM ON MICROARCHITECTURE, pp. 196–210.

By: Y. Hu*, M. Lokhandwala n, I. Te n & H. Tseng*

author keywords: Approximate Computing; Heterogeneous Computer Architectures/Systems; In-Storage Processing; Intelligent Storage Systems; Near-Data Processing
TL;DR: Varifocal Storage dynamically adjusts the dataset resolution within a storage device, thereby mitigating the performance bottleneck of exchanging/preparing data for approximate compute kernels and offers flexible, efficient support for approximate and exact computing without exceeding the costs of conventional storage systems. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Source: Web Of Science
Added: March 30, 2020

2019 article

GraphSSD: Graph Semantics Aware SSD

PROCEEDINGS OF THE 2019 46TH INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE (ISCA '19), pp. 116–128.

By: K. Matam*, G. Koo*, H. Zha*, H. Tseng n & M. Annavaram*

author keywords: SSD; Graphs; Flash storage
TL;DR: This paper proposes a graph semantic aware solid state drive (SSD) framework, called GraphSSD, which is a full system solution for storing, accessing, and performing graph analytics on SSDs and provides a simple programming interface that enables application developers to access graphs as native data in their applications, thereby simplifying the code development. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: April 14, 2020

2018 article

Pensieve: a Machine Learning Assisted SSD Layer for Extending the Lifetime

2018 IEEE 36TH INTERNATIONAL CONFERENCE ON COMPUTER DESIGN (ICCD), pp. 35–42.

By: I. Te n, M. Lokhandwala n, Y. Hu* & H. Tseng*

TL;DR: Pensieve is proposed, a machine-learning assisted SSD firmware layer that transparently helps reduce the demand for programs and erases, and efficiently classifies writing data into different compression categories without hints from software systems. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: February 25, 2019

2017 article

KAML: A Flexible, High-Performance Key-Value SSD

2017 23RD IEEE INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE COMPUTER ARCHITECTURE (HPCA), pp. 373–384.

TL;DR: KAML is presented, an SSD with a key-value interface that uses a novel multi-log architecture and stores data as variable-sized records rather than fixed-sized sectors and provides native transaction support tuned to support fine-grained locking. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2016 conference paper

Hippogriff: efficiently moving data in heterogeneous computing systems

Proceedings of the 34th ieee international conference on computer design (iccd), 376–379.

By: Y. Liu*, H. Tseng n, M. Gahagan*, J. Li*, Y. Jin* & S. Swanson*

TL;DR: Hippogriff is presented to provide a high-level programming model to simplify data movement between the compute and the storage, and to dynamically schedule data transfers based on system load to speedup single program workloads and save energy. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

2016 journal article

HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics

PROCEEDINGS OF THE VLDB ENDOWMENT, 9(14), 1647–1658.

By: J. Li*, H. Tseng*, C. Lin*, Y. Papakonstantinou* & S. Swanson*

TL;DR: HippogriffDB is proposed, an efficient, scalable GPU-accelerated OLAP system that adopts a query-over-block execution model that provides scalability using a stream-based approach and improves kernel efficiency with the operator fusion and double buffering mechanism. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2016 conference paper

Spmario: scale up mapreduce with i/o-oriented scheduling for the gpu

Proceedings of the 34th ieee international conference on computer design (iccd), 384–387.

By: Y. Liu*, H. Tseng n & S. Swanson*

TL;DR: Evaluation on a set of representative benchmarks against a highly-optimized baseline system shows that for the single job cases, SPMario can speedup job execution by up to 2.28×, and boost GPU utilization by 2.12× and 2.51× for I/O utilization. (via Semantic Scholar)
UN Sustainable Development Goal Categories
8. Decent Work and Economic Growth (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

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