Rachata Ausavarungnirun
Hardware and Architecture · 2013–2019
A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Hardware and Architecture — 89 citations into it; #1,522 of 1,551 by trust here, #642 by citations
- Computer Networks and Communications — 86 citations into it; #9,762 of 9,886 by trust here, #4,128 by citations
- Electrical and Electronic Engineering — 42 citations into it
- Information Systems — 31 citations into it
- Computer Vision and Pattern Recognition — 21 citations into it
- Artificial Intelligence — 19 citations into it
Whom Rachata Ausavarungnirun trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Onur Mutlu
- Yoongu Kim
- Thomas Moscibroda
- Stijn Eyerman
- Sai Prashanth Muralidhara
- Ali Bakhoda
- Scott Rixner
- Moinuddin K. Qureshi
- Vivek Seshadri
- Lieven Eeckhout
Who trusts Rachata Ausavarungnirun overall
Papers from Rachata Ausavarungnirun's perspective
Ordered by how strongly the researchers Rachata Ausavarungnirun trusts endorse each paper. Same corpus, a different order for every researcher.
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Memory Performance Attacks: Denial of Memory Service in Multi-Core Systems (USENIX Security Symposium)
- Memory access scheduling (Proceedings of 27th International Symposium on Computer Architecture (IEEE Cat. No.RS00201))
- Parallelism-Aware Batch Scheduling: Enhancing both Performance and Fairness of Shared DRAM Systems (International Symposium on Computer Architecture)
- ImageNet classification with deep convolutional neural networks
- The gem5 simulator (CARN)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Identity Mappings in Deep Residual Networks
- System-Level Performance Metrics for Multiprogram Workloads (IEEE Micro)
- Rodinia: A benchmark suite for heterogeneous computing
Their papers
- Google Workloads for Consumer Devices: Mitigating Data Movement Bottlenecks (2018) — 376 citations
- Processing Data Where It Makes Sense: Enabling In-Memory Computation (2019) — 318 citations
- MASK: Redesigning the GPU Memory Hierarchy to Support Multi-Application Concurrency (2018) — 119 citations
- RowClone: Fast and energy-efficient in-DRAM bulk data copy and initialization (2013) — 491 citations