The electrical power consumed by typical magnetic hard disk drives (HDD) not only increases linearly with the number of spindles but, more significantly, it increases as very fast power-laws of speed (RPM) and diameter. Since the theoretical basis fo
r this relationship is neither well-known nor readily accessible in the literature, we show how these exponents arise from aerodynamic disk drag and discuss their import for green storage capacity planning.
We show how to quantify scalability with the Universal Scalability Law (USL) by applying it to performance measurements of memcached, J2EE, and Weblogic on multi-core platforms. Since commercial multicores are essentially black-boxes, the accessible
performance gains are primarily available at the application level. We also demonstrate how our methodology can identify the most significant performance tuning opportunities to optimize application scalability, as well as providing an easy means for exploring other aspects of the multi-core system design space.
A parallel program can be represented as a directed acyclic graph. An important performance bound is the time to execute the critical path through the graph. We show how this performance metric is related to Amdahl speedup and the degree of average p
arallelism. These bounds formally exclude superlinear performance.
