ALEA: Fine-Grain Energy Profiling with Basic Block Sampling

Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.

Genomic instability in Chinese hamster cells after exposure to X rays or alpha particles of different mean linear energy transfer

Evidence has accumulated that radiation induces a transmissible persistent destabilization of the genome, which mag. result in effects arising in the progeny of irradiated but surviving cells. An enhanced death rate among the progeny of cells surviving irradiation persists for many generations in the form of a reduced plating efficiency. Such delayed reproductive death is correlated with an increased occurrence of micronuclei. Since it has been suggested that radiation-induced chromosomal instability might depend on the radiation quality, we investigated the effects of alpha particles of different LET by looking at the frequency of delayed micronuclei in Chinese hamster V79 cells after cytochalasin-induced block of cell division, A dose-dependent increase in the frequency of micronuclei was found in cells assayed 1 week postirradiation or later. Also, there was a persistent increase in the frequency of dicentrics in surviving irradiated cells, Moreover, we found an increased micronucleus frequency in all of the 30 clones isolated from individual cells which had been irradiated with doses equivalent to either one, two or three alpha-particle traversals per cell nucleus, We conclude that the target for genomic instability in Chinese hamster cells must be larger than the cell nucleus. (C) 1997 by Radiation Research Society

HERQULES:System level cross-layer design exploration for efficient energy-quality trade-offs

In this paper, we present a unique cross-layer design framework that allows systematic exploration of the energy-delay-quality trade-offs at the algorithm, architecture and circuit level of design abstraction for each block of a system. In addition, taking into consideration the interactions between different sub-blocks of a system, it identifies the design solutions that can ensure the least energy at the "right amount of quality" for each sub-block/system under user quality/delay constraints. This is achieved by deriving sensitivity based design criteria, the balancing of which form the quantitative relations that can be used early in the system design process to evaluate the energy efficiency of various design options. The proposed framework when applied to the exploration of energy-quality design space of the main blocks of a digital camera and a wireless receiver, achieves 58% and 33% energy savings under 41% and 20% error increase, respectively. © 2010 ACM.

Building sandstone surface modification by biofilm and iron precipitation: emerging block-scale heterogeneity and system response

Stone surfaces are sensitive to their environment. This means that they will often respond to exposure conditions by manifesting a change in surface characteristics. Such changes can be more than simply aesthetic, creating surface/subsurface heterogeneity in stone at the block scale, promoting stress gradients to be set up as surface response to, for example, temperature fluctuations, can diverge from subsurface response. This paper reports preliminary experiments investigating the potential of biofilms and iron precipitation as surface-modifiers on stone, exploring the idea of block-scale surface-to-depth heterogeneity, and investigating how physical alteration in the surface and near-surface zone can have implications for subsurface response and potentially for long-term decay patterns. Salt weathering simulations on fresh and surface-modified stone suggest that even subtle surface modification can have significant implications for moisture uptake and retention, salt concentration and distribution from surface to depth, over the period of the experimental run. The accumulation of salt may increase the retention of moisture, by modifying vapour pressure differentials and the rate of evaporation.
Temperature fluctuation experiments suggest that the presence of a biofilm can have an impact on energy transfer processes that occur at the stone surface (for example, buffering against temperature fluctuation), affecting surface-to-depth stress gradients. Ultimately, fresh and surface-modified blocks mask different kinds of system, which respond to inputs differently because of different storage mechanisms, encouraging divergent behaviour between fresh and surface modified stone over time.