More Like this

1. Computational Associative Memory Powered by Ferroelectric Memory

   https://doi.org/10.1109/DRC58590.2023.10187048  

   Ni, Kai ; Xiao, Yi ; Deng, Shan ; Narayanan, Vijaykrishnan ( June 2023 , IEEE)
2. Improving memory via automated targeted memory reactivation during sleep

   https://doi.org/10.1111/jsr.13731  

   Whitmore, Nathan W. ; Harris, Jasmine C. ; Kovach, Torin ; Paller, Ken A. ( December 2022 , Journal of Sleep Research)
3. Hardware Memory Management for Future Mobile Hybrid Memory Systems

   https://doi.org/10.1109/TCAD.2020.3012213  

   Wen, Fei ; Qin, Mian ; Gratz, Paul V. ; Reddy, A. L. ( November 2020 , IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems)

   null (Ed.)
4. TENET: Memory Safe and Fault Tolerant Persistent Transactional Memory}

   Madhava Krishnan Ramanathan ; Diyu Zhou ; Wook-Hee Kim ; Sudarsun Kannan ; Sanidhya Kashyap ; Changwoo Min ( February 2023 , 21st USENIX Conference on File and Storage Technologies)

   Ashvin Goel ; Dalit Naor (Ed.)

   Byte-addressable non-volatile memory (NVM) allows programs to directly access storage using memory interface without going through the expensive conventional storage stack. However, direct access to NVM makes the NVM data vulnerable to software bugs and hardware errors. This issue is critical because, unlike DRAM, corrupted data can persist forever, even after the system restart. Albeit the plethora of research on NVM programs and systems, there is little focus on protecting NVM data from software bugs and hardware errors. In this paper, we propose TENET, a new NVM programming framework, which guarantees memory safety and fault tolerance to protect NVM data against software bugs and hardware errors. TENET provides the popular persistent transactional memory (PTM) programming model. TENET leverages the concurrency guarantees (i.e., ACID properties) of PTM to provide performant and cost-efficient memory safety and fault tolerance. Our evaluations show that TENET offers an enhanced protection scope at a modest performance overhead and storage cost as compared to other PTMs with partial or no memory safety and fault tolerance support. 

   more » « less
5. Mnemo: Boosting Memory Cost Efficiency in Hybrid Memory Systems

   https://doi.org/10.1109/IPDPSW.2019.00080  

   Doudali, Thaleia Dimitra ; Gavrilovska, Ada ( January 2019 , Proceedings on IPDPS'19 Workshops, Workshop on High-Performance Big Data and Cloud Computing (HPBDC))

   For hosting data-serving and caching workloads based on key-value stores in clouds, the cost of memory represents a significant portion of the hosting expenses. The emergence of cheaper, but slower, types of memories, such as NVDIMMs, opens opportunities to reduce the hosting costs for such workloads. The question explored in this paper is how to determine adequate allocations of different memory types in future systems with heterogeneous memory components, so as to retain desired performance SLOs and maximize the cost efficiency of the memory resource. We develop Mnemo, a memory sizing and data tiering consultant, that permits quick exploration of the cost-benefit tradeoffs associated with different configurations of the hybrid memory components used by key-value store workloads. Using experimental evaluation with different workload patterns, Mnemo is able to afford applications such as Redis, Memcached and DynamoDB, with substantial reduction in their hosting costs, at negligible impact on application performance, thus improving the overall system memory cost efficiency. 

   more » « less