  Energy efficiency has been a daunting challenge for datacenters. The
financial industry operates some of the largest datacenters in the world. With
increasing energy costs and the financial services sector growth, emerging
financial analytics workloads may incur extremely high operational costs, to
meet their latency targets. Microservers have recently emerged as an
alternative to high-end servers, promising scalable performance and low energy
consumption in datacenters via scale-out. Unfortunately, stark differences in
architectural features, form factor and design considerations make a fair
comparison between servers and microservers exceptionally challenging. In this
paper we present a rigorous methodology and new metrics for fair comparison of
server and microserver platforms. We deploy our methodology and metrics to
compare a microserver with ARM cores against two servers with x86 cores,
running the same real-time financial analytics workload. We define
workload-specific but platform-independent performance metrics for platform
comparison, targeting both datacenter operators and end users. Our methodology
establishes that a server based the Xeon Phi processor delivers the highest
performance and energy-efficiency. However, by scaling out energy-efficient
microservers, we achieve competitive or better energy-efficiency than a
power-equivalent server with two Sandy Bridge sockets despite the microserver's
slower cores. Using a new iso-QoS (iso-Quality of Service) metric, we find that
the ARM microserver scales enough to meet market throughput demand, i.e. a 100%
QoS in terms of timely option pricing, with as little as 55% of the energy
consumed by the Sandy Bridge server.
