Publications by Donghyuk Lee

×

Status message

The Publications site is currently under construction, as a result some publications might be missing.

2017

Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, Cambridge, MA, USA, October 2017
DRAM cells in close proximity can fail depending on the data content in neighboring cells. These failures are called data-dependent failures. Detecting and mitigating these failures online, while the system is running in the field, enables various optimizations that improve reliability, latency, and energy efficiency of the system. For example, a system can improve performance and energy efficiency by using a lower refresh rate for most cells and mitigate the failing cells using higher refresh rates or error correcting codes. All these system optimizations depend on accurately detecting every possible data-dependent failure that could occur with any content in DRAM. Unfortunately, detecting all data-dependent failures requires the knowledge of DRAM internals specific to each DRAM chip. As internal DRAM architecture is not exposed to the system, detecting data-dependent failures at the system-level is a major challenge. In this paper, we decouple the detection and mitigation of data-dependent failures from physical DRAM organization such that it is possible to detect failures without knowledge of DRAM internals. To this end, we propose MEMCON, a memory content-based detection and mitigation mechanism for data-dependent failures in DRAM. MEMCON does not detect every possible data-dependent failure. Instead, it detects and mitigates failures that occur only with the current content in memory while the programs are running in the system. Such a mechanism needs to detect failures whenever there is a write access that changes the content of memory. As detection of failure with a runtime testing has a high overhead, MEMCON selectively initiates a test on a write, only when the time between two consecutive writes to that page (i.e., write interval) is long enough to provide significant benefit by lowering the refresh rate during that interval. MEMCON builds upon a simple, practical mechanism that predicts the long write intervals based on our observation that the write intervals in real workloads follow a Pareto distribution: the longer a page remains idle after a write, the longer it is expected to remain idle. Our evaluation shows that compared to a system that uses an aggressive refresh rate, MEMCON reduces refresh operations by 65--74%, leading to a 10%/17%/40% (min) to 12%/22%/50% (max) performance improvement for a single-core and 10%/23%/52% (min) to 17%/29%/65% (max) performance improvement for a 4-core system using 8/16/32 Gb DRAM chips.
@inproceedings{abc,
	abstract = {DRAM cells in close proximity can fail depending on the data content in neighboring cells. These failures are called data-dependent failures. Detecting and mitigating these failures online, while the system is running in the field, enables various optimizations that improve reliability, latency, and energy efficiency of the system. For example, a system can improve performance and energy efficiency by using a lower refresh rate for most cells and mitigate the failing cells using higher refresh rates or error correcting codes. All these system optimizations depend on accurately detecting every possible data-dependent failure that could occur with any content in DRAM. Unfortunately, detecting all data-dependent failures requires the knowledge of DRAM internals specific to each DRAM chip. As internal DRAM architecture is not exposed to the system, detecting data-dependent failures at the system-level is a major challenge.

In this paper, we decouple the detection and mitigation of data-dependent failures from physical DRAM organization such that it is possible to detect failures without knowledge of DRAM internals. To this end, we propose MEMCON, a memory content-based detection and mitigation mechanism for data-dependent failures in DRAM. MEMCON does not detect every possible data-dependent failure. Instead, it detects and mitigates failures that occur only with the current content in memory while the programs are running in the system. Such a mechanism needs to detect failures whenever there is a write access that changes the content of memory. As detection of failure with a runtime testing has a high overhead, MEMCON selectively initiates a test on a write, only when the time between two consecutive writes to that page (i.e., write interval) is long enough to provide significant benefit by lowering the refresh rate during that interval. MEMCON builds upon a simple, practical mechanism that predicts the long write intervals based on our observation that the write intervals in real workloads follow a Pareto distribution: the longer a page remains idle after a write, the longer it is expected to remain idle.

Our evaluation shows that compared to a system that uses an aggressive refresh rate, MEMCON reduces refresh operations by 65--74\%, leading to a 10\%/17\%/40\% (min) to 12\%/22\%/50\% (max) performance improvement for a single-core and 10\%/23\%/52\% (min) to 17\%/29\%/65\% (max) performance improvement for a 4-core system using 8/16/32 Gb DRAM chips.},
	author = {Samira Manabi Khan and Chris Wilkerson and Zhe Wang and Alaa R. Alameldeen and Donghyuk Lee and Onur Mutlu},
	booktitle = {Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture},
	title = {Detecting and mitigating data-dependent DRAM failures by exploiting current memory content},
	venue = {Cambridge, MA, USA},
	year = {2017}
}
Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, Cambridge, MA, USA, October 2017
Many important applications trigger bulk bitwise operations, i.e., bitwise operations on large bit vectors. In fact, recent works design techniques that exploit fast bulk bitwise operations to accelerate databases (bitmap indices, BitWeaving) and web search (BitFunnel). Unfortunately, in existing architectures, the throughput of bulk bitwise operations is limited by the memory bandwidth available to the processing unit (e.g., CPU, GPU, FPGA, processing-in-memory). To overcome this bottleneck, we propose Ambit, an Accelerator-in-Memory for bulk bitwise operations. Unlike prior works, Ambit exploits the analog operation of DRAM technology to perform bitwise operations completely inside DRAM, thereby exploiting the full internal DRAM bandwidth. Ambit consists of two components. First, simultaneous activation of three DRAM rows that share the same set of sense amplifiers enables the system to perform bitwise AND and OR operations. Second, with modest changes to the sense amplifier, the system can use the inverters present inside the sense amplifier to perform bitwise NOT operations. With these two components, Ambit can perform any bulk bitwise operation efficiently inside DRAM. Ambit largely exploits existing DRAM structure, and hence incurs low cost on top of commodity DRAM designs (1% of DRAM chip area). Importantly, Ambit uses the modern DRAM interface without any changes, and therefore it can be directly plugged onto the memory bus. Our extensive circuit simulations show that Ambit works as expected even in the presence of significant process variation. Averaged across seven bulk bitwise operations, Ambit improves performance by 32X and reduces energy consumption by 35X compared to state-of-the-art systems. When integrated with Hybrid Memory Cube (HMC), a 3D-stacked DRAM with a logic layer, Ambit improves performance of bulk bitwise operations by 9.7X compared to processing in the logic layer of the HMC. Ambit improves the performance of three real-world data-intensive applications, 1) database bitmap indices, 2) BitWeaving, a technique to accelerate database scans, and 3) bit-vector-based implementation of sets, by 3X-7X compared to a state-of-the-art baseline using SIMD optimizations. We describe four other applications that can benefit from Ambit, including a recent technique proposed to speed up web search. We believe that large performance and energy improvements provided by Ambit can enable other applications to use bulk bitwise operations.
@inproceedings{abc,
	abstract = {Many important applications trigger bulk bitwise operations, i.e., bitwise operations on large bit vectors. In fact, recent works design techniques that exploit fast bulk bitwise operations to accelerate databases (bitmap indices, BitWeaving) and web search (BitFunnel). Unfortunately, in existing architectures, the throughput of bulk bitwise operations is limited by the memory bandwidth available to the processing unit (e.g., CPU, GPU, FPGA, processing-in-memory).

To overcome this bottleneck, we propose Ambit, an Accelerator-in-Memory for bulk bitwise operations. Unlike prior works, Ambit exploits the analog operation of DRAM technology to perform bitwise operations completely inside DRAM, thereby exploiting the full internal DRAM bandwidth. Ambit consists of two components. First, simultaneous activation of three DRAM rows that share the same set of sense amplifiers enables the system to perform bitwise AND and OR operations. Second, with modest changes to the sense amplifier, the system can use the inverters present inside the sense amplifier to perform bitwise NOT operations. With these two components, Ambit can perform any bulk bitwise operation efficiently inside DRAM. Ambit largely exploits existing DRAM structure, and hence incurs low cost on top of commodity DRAM designs (1\% of DRAM chip area). Importantly, Ambit uses the modern DRAM interface without any changes, and therefore it can be directly plugged onto the memory bus.

Our extensive circuit simulations show that Ambit works as expected even in the presence of significant process variation. Averaged across seven bulk bitwise operations, Ambit improves performance by 32X and reduces energy consumption by 35X compared to state-of-the-art systems. When integrated with Hybrid Memory Cube (HMC), a 3D-stacked DRAM with a logic layer, Ambit improves performance of bulk bitwise operations by 9.7X compared to processing in the logic layer of the HMC. Ambit improves the performance of three real-world data-intensive applications, 1) database bitmap indices, 2) BitWeaving, a technique to accelerate database scans, and 3) bit-vector-based implementation of sets, by 3X-7X compared to a state-of-the-art baseline using SIMD optimizations. We describe four other applications that can benefit from Ambit, including a recent technique proposed to speed up web search. We believe that large performance and energy improvements provided by Ambit can enable other applications to use bulk bitwise operations.},
	author = {Vivek Seshadri and Donghyuk Lee and Thomas Mullins and Hasan Hassan and Amirali Boroumand and Jeremie Kim and Michael A. Kozuch and Onur Mutlu and Phillip B. Gibbons and Todd C. Mowry},
	booktitle = {Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture},
	title = {Ambit: in-memory accelerator for bulk bitwise operations using commodity DRAM technology},
	venue = {Cambridge, MA, USA},
	year = {2017}
}
Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA, June 2017
@inproceedings{abc,
	author = {Donghyuk Lee and Samira Manabi Khan and Lavanya Subramanian and Saugata Ghose and Rachata Ausavarungnirun and Gennady Pekhimenko and Vivek Seshadri and Onur Mutlu},
	booktitle = {Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA},
	title = {Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms.},
	url = {http://doi.acm.org/10.1145/3078505.3078533},
	year = {2017}
}
Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA, June 2017
@inproceedings{abc,
	author = {Kevin K. Chang and Abdullah Giray Yaglik{\c c}i and Saugata Ghose and Aditya Agrawal and Niladrish Chatterjee and Abhijith Kashyap and Donghyuk Lee and Mike O{\textquoteright}Connor and Hasan Hassan and Onur Mutlu},
	booktitle = {Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA},
	title = {Understanding Reduced-Voltage Operation in Modern DRAM Devices: Experimental Characterization, Analysis, and Mechanisms.},
	url = {http://doi.acm.org/10.1145/3078505.3078590},
	year = {2017}
}
2017 IEEE International Symposium on High Performance Computer Architecture, HPCA 2017, Austin, TX, USA, February 2017
@inproceedings{abc,
	author = {Hasan Hassan and Nandita Vijaykumar and Samira Manabi Khan and Saugata Ghose and Kevin K. Chang and Gennady Pekhimenko and Donghyuk Lee and Oguz Ergin and Onur Mutlu},
	booktitle = {2017 IEEE International Symposium on High Performance Computer Architecture, HPCA 2017, Austin, TX, USA},
	title = {SoftMC: A Flexible and Practical Open-Source Infrastructure for Enabling Experimental DRAM Studies.},
	url = {https://doi.org/10.1109/HPCA.2017.62},
	year = {2017}
}
CoRR, January 2017
@inproceedings{abc,
	author = {Kevin K. Chang and Abdullah Giray Yaglik{\c c}i and Saugata Ghose and Aditya Agrawal and Niladrish Chatterjee and Abhijith Kashyap and Donghyuk Lee and Mike O{\textquoteright}Connor and Hasan Hassan and Onur Mutlu},
	booktitle = {CoRR},
	title = {Understanding Reduced-Voltage Operation in Modern DRAM Chips: Characterization, Analysis, and Mechanisms.},
	url = {http://arxiv.org/abs/1705.10292},
	year = {2017}
}
POMACS, January 2017
@article{abc,
	author = {Kevin K. Chang and A. Giray Yaalik{\c c}i and Saugata Ghose and Aditya Agrawal and Niladrish Chatterjee and Abhijith Kashyap and Donghyuk Lee and Mike O{\textquoteright}Connor and Hasan Hassan and Onur Mutlu},
	journal = {POMACS},
	title = {Understanding Reduced-Voltage Operation in Modern DRAM Devices: Experimental Characterization, Analysis, and Mechanisms.},
	url = {http://doi.acm.org/10.1145/3084447},
	year = {2017}
}
POMACS, January 2017
@article{abc,
	author = {Donghyuk Lee and Samira Manabi Khan and Lavanya Subramanian and Saugata Ghose and Rachata Ausavarungnirun and Gennady Pekhimenko and Vivek Seshadri and Onur Mutlu},
	journal = {POMACS},
	title = {Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms.},
	url = {http://doi.acm.org/10.1145/3084464},
	year = {2017}
}

2016

Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science, Antibes Juan-Les-Pins, France, June 2016
@inproceedings{abc,
	author = {Kevin K. Chang and Abhijith Kashyap and Hasan Hassan and Saugata Ghose and Kevin Hsieh and Donghyuk Lee and Tianshi Li and Gennady Pekhimenko and Samira Manabi Khan and Onur Mutlu},
	booktitle = {Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science, Antibes Juan-Les-Pins, France},
	title = {Understanding Latency Variation in Modern DRAM Chips: Experimental Characterization, Analysis, and Optimization.},
	url = {http://doi.acm.org/10.1145/2896377.2901453},
	year = {2016}
}
46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016, Toulouse, France, June 2016
@inproceedings{abc,
	author = {Samira Manabi Khan and Donghyuk Lee and Onur Mutlu},
	booktitle = {46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016, Toulouse, France},
	title = {PARBOR: An Efficient System-Level Technique to Detect Data-Dependent Failures in DRAM.},
	url = {http://dx.doi.org/10.1109/DSN.2016.30},
	year = {2016}
}
2016 IEEE International Symposium on High Performance Computer Architecture, HPCA 2016, Barcelona, Spain, March 2016
@inproceedings{abc,
	author = {Kevin K. Chang and Prashant J. Nair and Donghyuk Lee and Saugata Ghose and Moinuddin K. Qureshi and Onur Mutlu},
	booktitle = {2016 IEEE International Symposium on High Performance Computer Architecture, HPCA 2016, Barcelona, Spain},
	title = {Low-Cost Inter-Linked Subarrays (LISA): Enabling fast inter-subarray data movement in DRAM.},
	url = {http://dx.doi.org/10.1109/HPCA.2016.7446095},
	year = {2016}
}
2016 IEEE International Symposium on High Performance Computer Architecture, HPCA 2016, Barcelona, Spain, March 2016
@inproceedings{abc,
	author = {Hasan Hassan and Gennady Pekhimenko and Nandita Vijaykumar and Vivek Seshadri and Donghyuk Lee and Oguz Ergin and Onur Mutlu},
	booktitle = {2016 IEEE International Symposium on High Performance Computer Architecture, HPCA 2016, Barcelona, Spain},
	title = {ChargeCache: Reducing DRAM latency by exploiting row access locality.},
	url = {http://dx.doi.org/10.1109/HPCA.2016.7446096},
	year = {2016}
}
IEEE Trans. Parallel Distrib. Syst., January 2016
@inproceedings{abc,
	author = {Lavanya Subramanian and Donghyuk Lee and Vivek Seshadri and Harsha Rastogi and Onur Mutlu},
	booktitle = {IEEE Trans. Parallel Distrib. Syst.},
	title = {BLISS: Balancing Performance, Fairness and Complexity in Memory Access Scheduling.},
	url = {http://dx.doi.org/10.1109/TPDS.2016.2526003},
	year = {2016}
}
CoRR, January 2016
@article{abc,
	author = {Donghyuk Lee and Samira Manabi Khan and Lavanya Subramanian and Rachata Ausavarungnirun and Gennady Pekhimenko and Vivek Seshadri and Saugata Ghose and Onur Mutlu},
	journal = {CoRR},
	title = {Reducing DRAM Latency by Exploiting Design-Induced Latency Variation in Modern DRAM Chips.},
	url = {http://arxiv.org/abs/1610.09604},
	year = {2016}
}
TACO, January 2016
@inproceedings{abc,
	author = {Donghyuk Lee and Saugata Ghose and Gennady Pekhimenko and Samira Manabi Khan and Onur Mutlu},
	booktitle = {TACO},
	title = {Simultaneous Multi-Layer Access: Improving 3D-Stacked Memory Bandwidth at Low Cost.},
	url = {http://doi.acm.org/10.1145/2832911},
	year = {2016}
}
CoRR, January 2016
@article{abc,
	author = {Vivek Seshadri and Donghyuk Lee and Thomas Mullins and Hasan Hassan and Amirali Boroumand and Jeremie Kim and Michael A. Kozuch and Onur Mutlu and Phillip B. Gibbons and Todd C. Mowry},
	journal = {CoRR},
	title = {Buddy-RAM: Improving the Performance and Efficiency of Bulk Bitwise Operations Using DRAM.},
	url = {http://arxiv.org/abs/1611.09988},
	year = {2016}
}
CoRR, January 2016
@article{abc,
	author = {Kevin Kai-Wei Chang and Donghyuk Lee and Zeshan Chishti and Alaa R. Alameldeen and Chris Wilkerson and Yoongu Kim and Onur Mutlu},
	journal = {CoRR},
	title = {Reducing Performance Impact of DRAM Refresh by Parallelizing Refreshes with Accesses.},
	url = {http://arxiv.org/abs/1601.06352},
	year = {2016}
}
CoRR, January 2016
@article{abc,
	author = {Donghyuk Lee and Yoongu Kim and Vivek Seshadri and Jamie Liu and Lavanya Subramanian and Onur Mutlu},
	journal = {CoRR},
	title = {Tiered-Latency DRAM (TL-DRAM).},
	url = {http://arxiv.org/abs/1601.06903},
	year = {2016}
}
CoRR, January 2016
@article{abc,
	author = {Donghyuk Lee and Yoongu Kim and Gennady Pekhimenko and Samira Manabi Khan and Vivek Seshadri and Kevin Kai-Wei Chang and Onur Mutlu},
	journal = {CoRR},
	title = {Adaptive-Latency DRAM (AL-DRAM).},
	url = {http://arxiv.org/abs/1603.08454},
	year = {2016}
}
CoRR, January 2016
@article{abc,
	author = {Yoongu Kim and Ross Daly and Jeremie Kim and Chris Fallin and Ji-Hye Lee and Donghyuk Lee and Chris Wilkerson and Konrad Lai and Onur Mutlu},
	journal = {CoRR},
	title = {RowHammer: Reliability Analysis and Security Implications.},
	url = {http://arxiv.org/abs/1603.00747},
	year = {2016}
}

2015

2015 International Conference on Parallel Architecture and Compilation, PACT 2015, San Francisco, CA, USA, October 2015
@inproceedings{abc,
	author = {Donghyuk Lee and Lavanya Subramanian and Rachata Ausavarungnirun and Jongmoo Choi and Onur Mutlu},
	booktitle = {2015 International Conference on Parallel Architecture and Compilation, PACT 2015, San Francisco, CA, USA},
	title = {Decoupled Direct Memory Access: Isolating CPU and IO Traffic by Leveraging a Dual-Data-Port DRAM.},
	url = {http://dx.doi.org/10.1109/PACT.2015.51},
	year = {2015}
}
21st IEEE International Symposium on High Performance Computer Architecture, HPCA 2015, Burlingame, CA, USA, February 2015
@inproceedings{abc,
	author = {Donghyuk Lee and Yoongu Kim and Gennady Pekhimenko and Samira Manabi Khan and Vivek Seshadri and Kevin Kai-Wei Chang and Onur Mutlu},
	booktitle = {21st IEEE International Symposium on High Performance Computer Architecture, HPCA 2015, Burlingame, CA, USA},
	title = {Adaptive-latency DRAM: Optimizing DRAM timing for the common-case.},
	url = {http://dx.doi.org/10.1109/HPCA.2015.7056057},
	year = {2015}
}
CoRR, January 2015
@article{abc,
	author = {Lavanya Subramanian and Donghyuk Lee and Vivek Seshadri and Harsha Rastogi and Onur Mutlu},
	journal = {CoRR},
	title = {The Blacklisting Memory Scheduler: Balancing Performance, Fairness and Complexity.},
	url = {http://arxiv.org/abs/1504.00390},
	year = {2015}
}
CoRR, January 2015
@article{abc,
	author = {Donghyuk Lee and Gennady Pekhimenko and Samira Manabi Khan and Saugata Ghose and Onur Mutlu},
	journal = {CoRR},
	title = {Simultaneous Multi Layer Access: A High Bandwidth and Low Cost 3D-Stacked Memory Interface.},
	url = {http://arxiv.org/abs/1506.03160},
	year = {2015}
}
Computer Architecture Letters, January 2015
@inproceedings{abc,
	author = {Vivek Seshadri and Kevin Hsieh and Amirali Boroumand and Donghyuk Lee and Michael A. Kozuch and Onur Mutlu and Phillip B. Gibbons and Todd C. Mowry},
	booktitle = {Computer Architecture Letters},
	title = {Fast Bulk Bitwise AND and OR in DRAM.},
	url = {http://dx.doi.org/10.1109/LCA.2015.2434872},
	year = {2015}
}

2014

32nd IEEE International Conference on Computer Design, ICCD 2014, Seoul, South Korea, October 2014
@inproceedings{abc,
	author = {Lavanya Subramanian and Donghyuk Lee and Vivek Seshadri and Harsha Rastogi and Onur Mutlu},
	booktitle = {32nd IEEE International Conference on Computer Design, ICCD 2014, Seoul, South Korea},
	title = {The Blacklisting Memory Scheduler: Achieving high performance and fairness at low cost.},
	url = {http://dx.doi.org/10.1109/ICCD.2014.6974655},
	year = {2014}
}
ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS '14, Austin, TX, June 2014
@inproceedings{abc,
	author = {Samira Manabi Khan and Donghyuk Lee and Yoongu Kim and Alaa R. Alameldeen and Chris Wilkerson and Onur Mutlu},
	booktitle = {ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS {\textquoteright}14, Austin, TX},
	title = {The efficacy of error mitigation techniques for DRAM retention failures: a comparative experimental study.},
	url = {http://doi.acm.org/10.1145/2591971.2592000},
	year = {2014}
}
ACM/IEEE 41st International Symposium on Computer Architecture, ISCA 2014, Minneapolis, MN, USA, June 2014
@inproceedings{abc,
	author = {Yoongu Kim and Ross Daly and Jeremie Kim and Chris Fallin and Ji-Hye Lee and Donghyuk Lee and Chris Wilkerson and Konrad Lai and Onur Mutlu},
	booktitle = {ACM/IEEE 41st International Symposium on Computer Architecture, ISCA 2014, Minneapolis, MN, USA},
	title = {Flipping bits in memory without accessing them: An experimental study of DRAM disturbance errors.},
	url = {http://dx.doi.org/10.1109/ISCA.2014.6853210},
	year = {2014}
}
20th IEEE International Symposium on High Performance Computer Architecture, HPCA 2014, Orlando, FL, USA, February 2014
@inproceedings{abc,
	author = {Kevin Kai-Wei Chang and Donghyuk Lee and Zeshan Chishti and Alaa R. Alameldeen and Chris Wilkerson and Yoongu Kim and Onur Mutlu},
	booktitle = {20th IEEE International Symposium on High Performance Computer Architecture, HPCA 2014, Orlando, FL, USA},
	title = {Improving DRAM performance by parallelizing refreshes with accesses.},
	url = {http://dx.doi.org/10.1109/HPCA.2014.6835946},
	year = {2014}
}

2013

The 46th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO-46, Davis, CA, USA, December 2013
@inproceedings{abc,
	author = {Vivek Seshadri and Yoongu Kim and Chris Fallin and Donghyuk Lee and Rachata Ausavarungnirun and Gennady Pekhimenko and Yixin Luo and Onur Mutlu and Phillip B. Gibbons and Michael A. Kozuch and Todd C. Mowry},
	booktitle = {The 46th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO-46, Davis, CA, USA},
	title = {RowClone: fast and energy-efficient in-DRAM bulk data copy and initialization.},
	url = {http://doi.acm.org/10.1145/2540708.2540725},
	year = {2013}
}
19th IEEE International Symposium on High Performance Computer Architecture, HPCA 2013, Shenzhen, China, February 2013
@inproceedings{abc,
	author = {Donghyuk Lee and Yoongu Kim and Vivek Seshadri and Jamie Liu and Lavanya Subramanian and Onur Mutlu},
	booktitle = {19th IEEE International Symposium on High Performance Computer Architecture, HPCA 2013, Shenzhen, China},
	title = {Tiered-latency DRAM: A low latency and low cost DRAM architecture.},
	url = {http://dx.doi.org/10.1109/HPCA.2013.6522354},
	year = {2013}
}
BMC Genomics, January 2013
@article{abc,
	author = {Hongyi Xin and Donghyuk Lee and Farhad Hormozdiari and Samihan Yedkar and Onur Mutlu and Can Alkan},
	journal = {BMC Genomics},
	title = {Accelerating read mapping with FastHASH.},
	url = {http://dx.doi.org/10.1186/1471-2164-14-S1-S13},
	year = {2013}
}

2012

39th International Symposium on Computer Architecture (ISCA 2012), Portland, OR, USA, June 2012
@inproceedings{abc,
	author = {Yoongu Kim and Vivek Seshadri and Donghyuk Lee and Jamie Liu and Onur Mutlu},
	booktitle = {39th International Symposium on Computer Architecture (ISCA 2012)},
	title = {A case for exploiting subarray-level parallelism (SALP) in DRAM.},
	url = {http://dx.doi.org/10.1109/ISCA.2012.6237032},
	venue = {Portland, OR, USA},
	year = {2012}
}