The (<i>unmentioned</i>) title of the paper is, "BlueDBM: an appliance for big data analytics"<p>Abstract:<p>><i>"Complex data queries, because of their need for random
accesses, have proven to be slow unless all the data can be
accommodated in DRAM. There are many domains, such as
genomics, geological data and daily twitter feeds where the
datasets of interest are 5TB to 20 TB. For such a dataset, one
would need a cluster with 100 servers, each with 128GB to
256GBs of DRAM, to accommodate all the data in DRAM.
On the other hand, such datasets could be stored easily in the
flash memory of a rack-sized cluster. Flash storage has much
better random access performance than hard disks, which
makes it desirable for analytics workloads. In this paper we
present BlueDBM, a new system architecture which has flash-
based storage with in-store processing capability and a low-
latency high-throughput inter-controller network. We show
that BlueDBM outperforms a flash-based system without these
features by a factor of 10 for some important applications.
While the performance of a ram-cloud system falls sharply
even if only 5%~10% of the references are to the secondary
storage, this sharp performance degradation is not an issue
in BlueDBM. BlueDBM presents an attractive point in the
cost-performance trade-off for Big Data analytics."</i><p><a href="http://people.csail.mit.edu/wjun/papers/ISCA15_Sang-Woo_Jun.pdf" rel="nofollow">http://people.csail.mit.edu/wjun/papers/ISCA15_Sang-Woo_Jun....</a>