``A distributed in-memory key-value store system on heterogeous CPU-GPU cluster" 

Kai zhang, Kaibo Wang, Yuan Yuan, Lei Guo, Rubao Lee, Xiaodong Zhang,  
Bingsheng He, Jiayu Hu, and Bei Hua

The VLDB Journal, August 2017, pp. 1-22. 
 

Abstract

In-memory key-value stores play a critical role in many data-intensive 
applications to provide high-throughput and low latency data accesses. 
In-memory key-value stores have several unique properties that include 
(1) data-intensive operations demanding high memory bandwidth for fast 
data accesses, (2) high data parallelism and simple computing operations 
demanding many slim parallel computing units, and (3) a large working set. 
However, our experiments show that homogeneous multicore CPU systems are 
increasingly mismatched to the special properties of key-value stores 
because they do not provide massive data parallelism and high memory 
bandwidth; the powerful but the limited number of computing cores does not 
satisfy the demand of the unique data processing task; and the cache 
hierarchy may not well benefit to the large working set. In this paper, 
we present the design and implementation of Mega-KV, a distributed in-memory 
key-value store system on a heterogeneous CPU–GPU cluster. Effectively 
utilizing the high memory bandwidth and latency hiding capability of GPUs, 
Mega-KV provides fast data accesses and significantly boosts overall 
performance and energy efficiency over the homogeneous CPU architectures. 
Mega-KV shows excellent scalability and processes up to 623-million 
key-value operations per second on a cluster installed with eight CPUs and 
eight GPUs, while delivering an efficiency of up to 299-thousand operations 
per Watt (KOPS/W).

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