Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Phase-change random access memory: a scalable technology
IBM Journal of Research and Development
Architecting phase change memory as a scalable dram alternative
Proceedings of the 36th annual international symposium on Computer architecture
A durable and energy efficient main memory using phase change memory technology
Proceedings of the 36th annual international symposium on Computer architecture
Scalable high performance main memory system using phase-change memory technology
Proceedings of the 36th annual international symposium on Computer architecture
Better I/O through byte-addressable, persistent memory
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Enhancing lifetime and security of PCM-based main memory with start-gap wear leveling
Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture
Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture
Dynamically replicated memory: building reliable systems from nanoscale resistive memories
Proceedings of the fifteenth edition of ASPLOS on Architectural support for programming languages and operating systems
Energy- and endurance-aware design of phase change memory caches
Proceedings of the Conference on Design, Automation and Test in Europe
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Scalability challenges of DRAM technology call for advances in emerging memory technologies, among which Phase Change Memory (PCM) has received considerable attention due to its non-volatility, storage density and capacity advantages. The drawbacks of PCM include limited write endurance and high power consumption for write operations (upto 10x in comparison to read operations). In this paper, we investigate new techniques that would perform writes to PCM with energy awareness. Our results show that we can minimize the write energy consumption by up to 8.1x by simply converting PCM native writes to read-before-write, and upto an additional 22.9% via intelligent out-of-position updates.