An Interpolative Analytical Cache Model with Application to Performance-Power Design Space Exploration

Caches are known to consume up to half of all system power in embedded processors. Co-optimizing performance and power of the cache subsystems is therefore an important step in the design of embedded systems, especially those employing application specific instruction processors. In this project, we propose an analytical cache model that succinctly captures the miss performance of an application over the entire cache parameter space. Unlike exhaustive trace driven simulation, our model requires that the program be simulated once so that a few key characteristics can be obtained. Using these application-dependent characteristics, the model can span the entire cache parameter space consisting of cache sizes, associativity and cache block sizes. In our unified model, we are able to cater for direct-mapped, set and fully associative instruction, data and unified caches. Validation against full trace-driven simulations shows that our model has a high degree of fidelity. Finally, we show how the model can be coupled with a power model for caches such that one can very quickly decide on pareto-optimal performance-power design points for rapid design space exploration.Singapore-MIT Alliance (SMA

Weighted fair caching: Occupancy-centric allocation for space-shared resources

10.1016/j.peva.2018.09.011Performance Evaluation Review463Performance Evaluation Revie

An Interpolative Analytical Cache Model with Application to Performance-Power Design Space Exploration

Abstract — Caches are known to consume up to half of all system power in embedded processors. Co-optimizing performance and power consumption of the cache subsystem is therefore an important step in the design of embedded systems, especially those employing application specific instruction processors. One of the main difficulty in such attempts is that cache behaviors are application as well as cache-structure specific. The two general approaches to tackling this problem is to either use exhaustive simulation or analytical modeling. The former is too time-consuming while the latter often lacks the required accuracy. In this paper, we introduce a novel third approach. We propose an analytical cache model that interpolates data from runs with direct mapped and fully associative caches so that the entire parameter space involving all set-associativity is spanned. Validation against full trace-driven simulations shows that our model has a very high degree of fidelity, but requires significantly less simulation time than exhaustive simulation. Furthermore, the model works for instruction, data or unified caches. Finally, we show how the model can be coupled with a power model for caches so that one can very quickly decide on pareto-optimal performance-power design points for rapid design space exploration

A Utility Optimization Approach to Network Cache Design

International audienceIn any caching system, the admission and eviction policies determine which contents are added and removed from a cache when a miss occurs. Usually, these policies are devised so as to mitigate staleness and increase the hit probability. Nonetheless, the utility of having a high hit probability can vary across contents. This occurs, for instance, when service level agreements must be met, or if certain contents are more difficult to obtain than others. In this paper, we propose utility-driven caching, where we associate with each content a utility, which is a function of the corresponding content hit probability. We formulate optimization problems where the objectives are to maximize the sum of utilities over all contents. These problems differ according to the stringency of the cache capacity constraint. Our framework enables us to reverse engineer classical replacement policies such as LRU and FIFO, by computing the utility functions that they maximize. We also develop online algorithms that can be used by service providers to implement various caching policies based on arbitrary utility functions

A utility optimization approach to network cache design

International audienceIn any caching system, the admission and eviction policies determine which contents are added and removed from a cache when a miss occurs. Usually, these policies are devised so as to mitigate staleness and increase the hit probability. Nonetheless, the utility of having a high hit probability can vary across contents. This occurs, for instance, when service level agreements must be met, or if certain contents are more difficult to obtain than others. In this paper, we propose utility-driven caching, where we associate with each content a utility, which is a function of the corresponding content hit probability. We formulate optimization problems where the objectives are to maximize the sum of utilities over all contents. These problems differ according to the stringency of the cache capacity constraint. Our framework enables us to reverse engineer classical replacement policies such as LRU and FIFO, by computing the utility functions that they maximize. We also develop online algorithms that can be used by service providers to implement various caching policies based on arbitrary utility functions

Induction of Myogenic Differentiation of Human Mesenchymal Stem Cells Cultured on Notch Agonist (Jagged-1) Modified Biodegradable Scaffold Surface

Engineered scaffold surface provides stem cells with vital cues that could determine the eventual fate of stem cells. In this work, biodegradable poly­(l-lactide-<i>co</i>-ε-caprolactone) (PLCL) scaffold conjugated with Notch agonist-Jagged-1­(JAG) peptide (2.1 kDa) was prepared to initiate myogenic differentiation of human mesenchymal stem cells (hMSCs). The scaffold surface was activated with oxygen plasma and acrylic acid was engrafted via UV polymerization to form a surface bearing carboxylic groups. JAG peptide was subsequently immobilized onto the carboxylated scaffold surface. Surface chemistry and topography were examined using attenuated total reflection Fourier transform infrared, X-ray photoelectron spectroscopy, and atomic force microscopy. Quantitative real time polymerase chain reaction analysis revealed activation of the Notch pathway; furthermore, several specific markers associated with myogenic but not osteogenic differentiation were shown to be up-regulated in hMSCs cultured on the engineered surface. The pro-myocardial effect of surface bound JAG peptide was further affirmed via immunodetection of the distinct myocardial marker, cardiac troponin T. Collectively, our results suggest that PLCL conjugated JAG peptide is a viable strategy to enhance the functional potential of scaffolds to be used as a bioengineered cardiac patch in myocardial infarction repair