Constructing energy-efficient database systems to reduce economic costs and
environmental impact has been studied for 10 years. With the emergence of the big data …

High-performance flash-based key-value stores in data-centers utilize large amounts of
DRAM to cache hot data. However, motivated by the high cost and power consumption of …

Modern data-parallel systems such as Spark rely increasingly on in-memory computing that
can significantly improve the efficiency of iterative algorithms. To process real-world …

The current mobile applications have rapidly growing memory footprints, posing a great
challenge for memory system design. Insufficient DRAM main memory will incur frequent …

Traditional scientific and emerging data analytics applications require fast, power-efficient,
large, and persistent memories. Combining all these characteristics within a single memory …

Hybrid memory systems, comprised of emerging non-volatile memory (NVM) and DRAM,
have been proposed to address the growing memory demand of current mobile …

Abstract Non-Volatile Main Memories (NVMMs) have recently emerged as a promising
technology for future memory systems. Generally, NVMMs have many desirable properties …

Hybrid memory systems composed of emerging non-volatile memory (NVM) and DRAM
have drawn increasing attention in recent years. To fully exploit the advantages of both NVM …

Non-Volatile Memories (NVMs) require security mechanisms, eg, counter mode encryption
and integrity tree verification, which are important to protect systems in terms of encryption …

High-performance flash-based key-value stores in data-centers utilize large amounts of
DRAM to cache hot data. However, motivated by the high cost and power consumption of …