June 14th, 2017

Cache replacement and branch prediction are two important microarchitectural prediction techniques for improving performance. We propose a data-driven approach to designing microarchitectural predictors. Through simulation, we collect traces giving detailed control-flow and memory behavior. Then use stochastic search techniques, such as genetic algorithms, to find points in a large design space of predictors that yield good accuracy on the traces. We then evaluate the predictors on held-out data. This talk will present two techniques resulting from this methodology. In Multiperspective Branch Prediction, many features and their parameters are tuned using a genetic algorithm to yield a very accurate perceptron-based branch predictor. Multiperspective Reuse Prediction uses the same idea for cache management. Many features of memory accesses to predict the reuse of a given memory access. The features and their parameters are chosen by a stochastic search yielding a very accurate predictor. This predictor is applied to a placement, replacement, and bypass optimization that out-performs the state of the art

Language of Interview and the Subjectively-Rated Health of Hispanic Mothers and their Children

Hispanics tend to be as healthy as non-Hispanic whites across a number of indicators, yet they consistently rate their health as worse than non-Hispanic whites. This incongruous finding has been tied both to levels of acculturation and Spanish-language use, questioning the validity of self-reported health for Spanish speakers in the United States. Furthermore, in the same way that Hispanic adults interviewed in Spanish have worse self-rated health, when asked in Spanish mothers rate their children’s health as worse than those mothers who answer in English. The exact reasons for this relationship, though, are unclear. Frequently this language effect has been taken as an indicator of acculturation; as such, the assumption is that as time progresses Hispanics become more acculturated and answer questions regarding their health more similarly to non-Hispanic whites. However, up until this point there has been no longitudinal research examining the relationship between rated health and language of interview. Using three waves of data on Hispanic mothers and their children from the Fragile Families and Child Well-being Study, this paper addresses the following questions: 1. Is Spanish language interview predictive of worse rated health for both mothers and children, and do these relationships change over time? 2. Does the effect of language on rated health persist after controlling for potential mediators? By employing two-level generalized linear models, we find that on average, those who were interviewed in Spanish are more likely to rate their and their children’s health as worse than those who answered in English. The effect of language of interview on reported health persists over time, even after controlling for measures of acculturation, physical and mental health, and access to health care. Contrary to what some have proposed, we see no discernable change over time in the way women rate their own health or that of their children.

Climate change impact on endangered cloud forest tree species in Mexico

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Ecological niche models have seen intensive exploration as a tool in biodiversity conservation and evaluation of areas for designing protected natural areas systems, including projections of potential distributions under future conditions. Cloud forest is the most endangered ecosystem in Mexico, and yet ranks high in terms of diversity and endemism. This study focuses on 12 endangered and range-restricted tree species in Mexican cloud forests, exploring patterns of distribution and diversity under 2 future emissions scenarios (representative concentration pathways 4.5 and 8.5) as anticipated by 20 general circulation models. Our results indicate a likely strong reduction in species’ distributional areas and —consequently— species diversity manifested in different cloud forest patches across the country. The genus Quercus resulted the most sensitive to climate change. We identified cloud forest patches that are most vulnerable to climate change effects, which can and should focus priorities for protection of this ecosystem, particularly in the Sierra Madre Oriental, where cloud forest is presently lacking any protection

Kinetics and crystallization path of a Fe-based metallic glass alloy

The thermal stability and the quantification of the different transformation processes involved in the overall crystallization of the Fe50Cr15Mo14C15B6 amorphous alloy were investigated by several characterization techniques. Formation of various metastable and stable phases during the devitrification process in the sequence a-Fe, ¿-Cr6Fe18Mo5, M23(C,B)6, M7C3, ¿-Fe3Mo3C and FeMo2B2 (with M = Fe, Cr, Mo), was observed by in-situ synchrotron high energy X-ray diffraction and in-situ transmission electron microscopy. By combining these techniques with differential scanning calorimetry data, the crystallization states and their temperature range of stability under continuous heating were related with the evolution of the crystallized fraction and the phase sequence as a function of temperature, revealing structural and chemical details of the different transformation mechanisms.Postprint (published version

Rebasing Microarchitectural Research with Industry Traces

Microarchitecture research relies on performance models with various degrees of accuracy and speed. In the past few years, one such model, ChampSim, has started to gain significant traction by coupling ease of use with a reasonable level of detail and simulation speed. At the same time, datacenter class workloads, which are not trivial to set up and benchmark, have become easier to study via the release of hundreds of industry traces following the first Championship Value Prediction (CVP-1) in 2018. A tool was quickly created to port the CVP-1 traces to the ChampSim format, which, as a result, have been used in many recent works. In this paper, we revisit this conversion tool and find that several key aspects of the CVP-1 traces are not preserved by the conversion. We therefore propose an improved converter that addresses most conversion issues as well as patches known limitations of the CVP-1 traces themselves. We evaluate the impact of our changes on two commits of ChampSim, with one used for the first Instruction Championship Prefetching (IPC-1) in 2020. We find that the performance variation stemming from higher accuracy conversion is significant

Stem Cell Fate Determination during Development and Regeneration of Ectodermal Organs

The development of ectoderm-derived appendages results in a large variety of highly specialized organs such as hair follicles, mammary glands, salivary glands, and teeth. Despite varying in number, shape, and function, all these ectodermal organs develop through continuous and reciprocal epithelial–mesenchymal interactions, sharing common morphological and molecular features especially during their embryonic development. Diseases such as ectodermal dysplasias can affect simultaneously these organs, suggesting that they may arise from common multipotent precursors residing in the embryonic ectoderm. During embryogenesis, these putative ectodermal stem cells may adopt different fates and consequently be able to generate a variety of tissue-specific stem cells, which are the sources for the various cell lineages that form the diverse organs. The specification of those common epithelial precursors, as well as their further lineage commitment to tissue-specific stem cells, might be controlled by specific signals. It has been well documented that Notch, Wnt, bone morphogenetic protein, and fibroblast growth factor signaling pathways regulate cell fate decisions during the various stages of ectodermal organ development. However, the in vivo spatial and temporal dynamics of these signaling pathways are not yet well understood. Improving the current knowledge on the mechanisms involved in stem cell fate determination during organogenesis and homeostasis of ectodermal organs is crucial to develop effective stem cell-based therapies in order to regenerate or replace pathological and damaged tissues

MILP models for objective reduction in multi-objective optimization: Error measurement considerations and non-redundancy ratio

A common approach in multi-objective optimization (MOO) consists of removing redundant objectives or reducing the set of objectives minimizing some metrics related with the loss of the dominance structure. In this paper, we comment some weakness related to the usual minimization of the maximum error (infinity norm or δ-error) and the convenience of using a norm 1 instead. Besides, a new model accounting for the minimum number of Pareto solutions that are lost when reducing objectives is provided, which helps to further describe the effects of the objective reduction in the system. A comparison of the performance of these algorithms and its usefulness in objective reduction against principal component analysis + Deb & Saxena's algorithm (Deb & Saxena Kumar, 2005) is provided, and the ability of combining it with a principal component analysis in order to reduce the dimensionality of a system is also studied and commented.The authors acknowledge financial support from the Spanish “Ministerio de Economía, Industria y Competitividad” (CTQ2016-77968-C3-2-P, AEI/FEDER, UE)

Morrigan: A Composite Instruction TLB Prefetcher

The effort to reduce address translation overheads has typically targeted data accesses since they constitute the overwhelming portion of the second-level TLB (STLB) misses in desktop and HPC applications. The address translation cost of instruction accesses has been relatively neglected due to historically small instruction footprints. However, state-of-the-art datacenter and server applications feature massive instruction footprints owing to deep software stacks, resulting in high STLB miss rates for instruction accesses. This paper demonstrates that instruction address translation is a performance bottleneck in server workloads. In response, we propose Morrigan, a microarchitectural instruction STLB prefetcher whose design is based on new insights regarding instruction STLB misses. At the core of Morrigan there is an ensemble of table-based Markov prefetchers that build and store variable length Markov chains out of the instruction STLB miss stream. Morrigan further employs a sequential prefetcher and a scheme that exploits page table locality to maximize miss coverage. An important contribution of the work is showing that access frequency is more important than access recency when choosing replacement candidates. Based on this insight, Morrigan introduces a new replacement policy that identifies victims in the Markov prefetchers using a frequency stack while adapting to phase-change behavior. On a set of 45 industrial server workloads, Morrigan eliminates 69% of the memory references in demand page walks triggered by instruction STLB misses and improves geometric mean performance by 7.6%.This work is partially supported by the Spanish Ministry of Science and Technology through the PID2019-107255GB project, the Generalitat de Catalunya (contract 2017-SGR-1414), the NSF grant CCF-1912617, the Semiconductor Research Corporation grant 2936.001, and generous gifts from Intel Labs. Georgios Vavouliotis has been supported by the Spanish Ministry of Economy, Industry and Competitiveness and the European Social Fund under the FPI fellowship No. PRE2018-087046. Marc Casas has been supported by the Spanish Ministry of Economy, Industry and Competitiveness under the Ramon y Cajal fellowship No. RYC-2017-23269.Peer ReviewedPostprint (author's final draft

Balanced-chromatic number and Hadwiger-like conjectures

Motivated by different characterizations of planar graphs and the 4-Color Theorem, several structural results concerning graphs of high chromatic number have been obtained. Toward strengthening some of these results, we consider the \emph{balanced chromatic number}, $\chi_b(\hat{G})$, of a signed graph $\hat{G}$. This is the minimum number of parts into which the vertices of a signed graph can be partitioned so that none of the parts induces a negative cycle. This extends the notion of the chromatic number of a graph since $\chi(G)=\chi_b(\tilde{G})$, where $\tilde{G}$ denotes the signed graph obtained from~$G$ by replacing each edge with a pair of (parallel) positive and negative edges. We introduce a signed version of Hadwiger's conjecture as follows. Conjecture: If a signed graph $\hat{G}$ has no negative loop and no $\tilde{K_t}$-minor, then its balanced chromatic number is at most $t-1$. We prove that this conjecture is, in fact, equivalent to Hadwiger's conjecture and show its relation to the Odd Hadwiger Conjecture. Motivated by these results, we also consider the relation between subdivisions and balanced chromatic number. We prove that if $(G, \sigma)$ has no negative loop and no $\tilde{K_t}$-subdivision, then it admits a balanced $\frac{79}{2}t^2$-coloring. This qualitatively generalizes a result of Kawarabayashi (2013) on totally odd subdivisions