Cache Events Research Articles

Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding.

Forming an episodic memory requires binding together disparate elements that co-occur in a single experience. One model of this process is that neurons representing different components of a memory bind to an "index" - a subset of neurons unique to that memory. Evidence for this model has recently been found in chickadees, which use hippocampal memory to store and recall locations of cached food. Chickadee hippocampus produces sparse, high-dimensional patterns ("barcodes") that uniquely specify each caching event. Unexpectedly, the same neurons that participate in barcodes also exhibit conventional place tuning. It is unknown how barcode activity is generated, and what role it plays in memory formation and retrieval. It is also unclear how a memory index (e.g. barcodes) could function in the same neural population that represents memory content (e.g. place). Here, we design a biologically plausible model that generates barcodes and uses them to bind experiential content. Our model generates barcodes from place inputs through the chaotic dynamics of a recurrent neural network and uses Hebbian plasticity to store barcodes as attractor states. The model matches experimental observations that memory indices (barcodes) and content signals (place tuning) are randomly intermixed in the activity of single neurons. We demonstrate that barcodes reduce memory interference between correlated experiences. We also show that place tuning plays a complementary role to barcodes, enabling flexible, contextually-appropriate memory retrieval. Finally, our model is compatible with previous models of the hippocampus as generating a predictive map. Distinct predictive and indexing functions of the network are achieved via an adjustment of global recurrent gain. Our results suggest how the hippocampus may use barcodes to resolve fundamental tensions between memory specificity (pattern separation) and flexible recall (pattern completion) in general memory systems.

Barcoding of episodic memories in the hippocampus of a food-caching bird

The hippocampus is critical for episodic memory. Although hippocampal activity represents place and other behaviorally relevant variables, it is unclear how it encodes numerous memories of specific events in life. To study episodic coding, we leveraged the specialized behavior of chickadees-food-caching birds that form memories at well-defined moments in time whenever they cache food for subsequent retrieval. Our recordings during caching revealed very sparse, transient barcode-like patterns of firing across hippocampal neurons. Each "barcode" uniquely represented a caching event and transiently reactivated during the retrieval of that specific cache. Barcodes co-occurred with the conventional activity of place cells but were uncorrelated even for nearby cache locations that had similar place codes. We propose that animals recall episodic memories by reactivating hippocampal barcodes. Similarly to computer hash codes, these patterns assign unique identifiers to different events and could be a mechanism for rapid formation and storage of many non-interfering memories.

Computational models of episodic-like memory in food-caching birds

Birds of the crow family adapt food-caching strategies to anticipated needs at the time of cache recovery and rely on memory of the what, where and when of previous caching events to recover their hidden food. It is unclear if this behavior can be explained by simple associative learning or if it relies on higher cognitive processes like mental time-travel. We present a computational model and propose a neural implementation of food-caching behavior. The model has hunger variables for motivational control, reward-modulated update of retrieval and caching policies and an associative neural network for remembering caching events with a memory consolidation mechanism for flexible decoding of the age of a memory. Our methodology of formalizing experimental protocols is transferable to other domains and facilitates model evaluation and experiment design. Here, we show that memory-augmented, associative reinforcement learning without mental time-travel is sufficient to explain the results of 28 behavioral experiments with food-caching birds.

Vizard: Passing Over Profiling-Based Detection by Manipulating Performance Counters

Cache side-channel attacks have been serious security threats to server computer systems, thus researchers have proposed software-based defense approaches that can detect the security attacks. Profiling-based detectors are lightweight detection solutions that rely on hardware performance counters to identify unique cache performance behaviors by cache side-channel attacks. The detectors typically need to set appropriate criteria to differentiate between attack processes and normal applications. In this paper, we explore the limitations of profiling-based detectors that rely on hardware performance counters.We present an attack scenario, called Vizard, that can bypass the existing profiling-based detectors by manipulating cache performance behaviors of an attack process. Our analysis discloses that cache side-channel attacks include idle periods that can be exploited as attack windows for creating cache events. Vizard generates counterbalancing cache events within the attack windows to hide particular cache performance behaviors of cache side-channel attacks. Our evaluation exhibits that Vizard can effectively bypass profiling-based detectors while maintaining high attack success rates. Our research work represents that attackers can bypass the existing detection approaches by manipulating performance counters.

Cross-World Covert Channel on ARM Trustzone through PMU.

The TrustZone technology is incorporated in a majority of recent ARM Cortex A and Cortex M processors widely deployed in the IoT world. Security critical code execution inside a so-called secure world is isolated from the rest of the application execution within a normal world. It provides hardware-isolated area called a trusted execution environment (TEE) in the processor for sensitive data and code. This paper demonstrates a vulnerability in the secure world in the form of a cross-world, secure world to normal world, covert channel. Performance counters or Performance Monitoring Unit (PMU) events are used to convey the information from the secure world to the normal world. An encoding program generates appropriate PMU event footprint given a secret S. A corresponding decoding program reads the PMU footprint and infers S using machine learning (ML). The machine learning model can be trained entirely from the data collected from the PMU in user space. Lack of synchronization between PMU start and PMU read adds noise to the encoding/decoding ML models. In order to account for this noise, this study proposes three different synchronization capabilities between the client and trusted applications in the covert channel. These are synchronous, semi-synchronous, and asynchronous. Previously proposed PMU based covert channels deploy L1 and LLC cache PMU events. The latency of these events tends to be 100–1000 cycles limiting the bandwidth of these covert channels. We propose to use microarchitecture level events with latency of 10–100 cycles captured through PMU for covert channel encoding leading to a potential 100× higher bandwidth. This study conducts a series of experiments to evaluate the proposed covert channels under various synchronization models on a TrustZone supported Cortex-A processor using OP-TEE framework. As stated earlier, switch from signaling based on PMU cache events to PMU microarchitectural events leads to approximately 15× higher covert channel bandwidth. This proposed finer-grained microarchitecture event encoding covert channel can achieve throughput of the order of 11 Kbits/s as opposed to previous work’s throughput of the order of 760 bits/s.

Digging into the behaviour of an active hunting predator: arctic fox prey caching events revealed by accelerometry

BackgroundBiologging now allows detailed recording of animal movement, thus informing behavioural ecology in ways unthinkable just a few years ago. In particular, combining GPS and accelerometry allows spatially explicit tracking of various behaviours, including predation events in large terrestrial mammalian predators. Specifically, identification of location clusters resulting from prey handling allows efficient location of killing events. For small predators with short prey handling times, however, identifying predation events through technology remains unresolved. We propose that a promising avenue emerges when specific foraging behaviours generate diagnostic acceleration patterns. One such example is the caching behaviour of the arctic fox (Vulpes lagopus), an active hunting predator strongly relying on food storage when living in proximity to bird colonies.MethodsWe equipped 16 Arctic foxes from Bylot Island (Nunavut, Canada) with GPS and accelerometers, yielding 23 fox-summers of movement data. Accelerometers recorded tri-axial acceleration at 50 Hz while we obtained a sample of simultaneous video recordings of fox behaviour. Multiple supervised machine learning algorithms were tested to classify accelerometry data into 4 behaviours: motionless, running, walking and digging, the latter being associated with food caching. Finally, we assessed the spatio-temporal concordance of fox digging and greater snow goose (Anser caerulescens antlanticus) nesting, to test the ecological relevance of our behavioural classification in a well-known study system dominated by top-down trophic interactions.ResultsThe random forest model yielded the best behavioural classification, with accuracies for each behaviour over 96%. Overall, arctic foxes spent 49% of the time motionless, 34% running, 9% walking, and 8% digging. The probability of digging increased with goose nest density and this result held during both goose egg incubation and brooding periods.ConclusionsAccelerometry combined with GPS allowed us to track across space and time a critical foraging behaviour from a small active hunting predator, informing on spatio-temporal distribution of predation risk in an Arctic vertebrate community. Our study opens new possibilities for assessing the foraging behaviour of terrestrial predators, a key step to disentangle the subtle mechanisms structuring many predator–prey interactions and trophic networks.

Food caching by bears: A literature review and new observations for Asiatic and American black bears

Food caching is a common behavior for many mammals, but less is known about the prevalence and importance of food caching for some species. Here we report the first documented caching events by Asiatic black bears (Ursus thibetanus, n = 5) in Japan and 3 additional caching events by American black bears (U. americanus) in California, USA. We also performed a systematic literature review on caching by bears as a reference point for future investigations. Caching was most frequently reported for brown bears (U. arctos), and most caching by bears occurred with large prey. Caching is most likely used to protect large carcasses from spoiling or detection by scavengers, allowing bears to consume more of the carcass. The lack of published studies on caching by bears may be due to the behavior being infrequently used and difficult to record. We encourage an increase, but also consistency, in future reporting, including specific descriptions of caching behavior.

Using Actor-Network Theory to Characterize the Production of Ancient Maya Caching Events at Cerro Maya (Cerros, Belize)

Inspired by actor-network theory, this research uses an operationalized archaeological actor-network approach to characterize and examine human-object relationships associated with ritual caching deposits (votive bundles of objects) at the site of Cerro Maya (formerly Cerros), Belize. Designed to be broadly applicable for archaeological studies, our archaeological actor-network approach made it possible to inductively examine, characterize, and diachronically compare the complex arrays of human and nonhuman relationships. In contrast to previous studies that characterized caches mainly in symbolic terms, we treated caches as traces of the small-scale actor-networks that emerged during the production of ancient Maya caching events. More specifically, our actor-network methodology made it possible to characterize caches and caching events in terms of the relationships between materials, temporality, objects, places, and groups of people, their intentions, and actions. The inductive and diachronic focus of approach also allowed us to compare arrays of caching actor-networks over time while considering the social affect that caching events had on subsequent caching events and the site’s social development. This approach demonstrates that even simple artifact clusters can be viewed as proxies for highly complex networks of interlinked social relations that play roles in shaping important historical interactions and social orders over time.

A small cat saving food for later: caching behavior in the European wildcat (Felis silvestris silvestris)

Caching behavior consists on the relocation or storage of food to protect it from competitors, to delay food spoilage, or to exploit it during times of scarcity. While this behavior has been widely described for some medium and large-sized felids, only a few cases documented caching behavior in small felids. Here, we provide the first exhaustive description of a caching event on a European wildcat in the Cantabrian Mountains (NW Spain). The wildcat behaved like a lynx/puma, visiting a road-killed roe deer carcass at least 9 days along a 21-day period, consuming the main muscles and covering it with hair and vegetation.

Dynamic Probabilistic Caching Algorithm with Content Priorities for Content-Centric Networks

This paper presents a caching algorithm that offers better reconstructed data quality to the requesters than a probabilistic caching scheme while maintaining comparable network performance. It decides whether an incoming data packet must be cached based on the dynamic caching probability, which is adjusted according to the priorities of content carried by the data packet, the uncertainty of content popularities, and the records of cache events in the router. The adaptation of caching probability depends on the priorities of content, the multiplication factor adaptation, and the addition factor adaptation. The multiplication factor adaptation is computed from an instantaneous cache-hit ratio, whereas the addition factor adaptation relies on a multiplication factor, popularities of requested contents, a cache-hit ratio, and a cache-miss ratio. We evaluate the performance of the caching algorithm by comparing it with previous caching schemes in network simulation. The simulation results indicate that our proposed caching algorithm surpasses previous schemes in terms of data quality and is comparable in terms of network performance.

California scrub-jays reduce visual cues available to potential pilferers by matching food colour to caching substrate.

Some animals hide food to consume later; however, these caches are susceptible to theft by conspecifics and heterospecifics. Caching animals can use protective strategies to minimize sensory cues available to potential pilferers, such as caching in shaded areas and in quiet substrate. Background matching (where object patterning matches the visual background) is commonly seen in prey animals to reduce conspicuousness, and caching animals may also use this tactic to hide caches, for example, by hiding coloured food in a similar coloured substrate. We tested whether California scrub-jays (Aphelocoma californica) camouflage their food in this way by offering them caching substrates that either matched or did not match the colour of food available for caching. We also determined whether this caching behaviour was sensitive to social context by allowing the birds to cache when a conspecific potential pilferer could be both heard and seen (acoustic and visual cues present), or unseen (acoustic cues only). When caching events could be both heard and seen by a potential pilferer, birds cached randomly in matching and non-matching substrates. However, they preferentially hid food in the substrate that matched the food colour when only acoustic cues were present. This is a novel cache protection strategy that also appears to be sensitive to social context. We conclude that studies of cache protection strategies should consider the perceptual capabilities of the cacher and potential pilferers.

The Clark Creek Cache in West-Central Montana

The majority of Precontact lithic caches from Montana cannot be chronologically placed, because they lack primary context with radiometrically datable organics or are not composed of obsidian, a datable natural glass. Dated obsidian from caches can also be positively traced to its geologic source. A rare such cache of largely obsidian pieces was found on the Sieben Ranch in 2011. Forty-three obsidian flakes and four chert flakes were observed partially exposed inside a 21-cm-diameter pit. X-ray dispersive fluorescence analysis attributed obsidian to the Bear Gulch source in the Centennial Mountains area of southwestern Montana and southeastern Idaho, approximately 280 km distant. Hydration dating suggests that the caching event occurred c. 444 ± 18 hydration years before present (HYBP). The unidirectional core technology applied to produce the majority of the pieces and the resulting large, curved, blade-like, retouched flakes is unexpected for the Late Precontact Period in the Northern Plains and Intermountain Regions.

A comprehensive study of multiple deductions-based algebraic trace driven cache attacks on AES

Existing trace driven cache attacks (TDCAs) can only analyze the cache events in the first two rounds or the last round of AES, which limits the efficiency of the attacks. Recently, Zhao et al. proposed the multiple deductions-based algebraic side-channel attack (MDASCA) to cope with the errors in leakage measurements and to exploit new leakage models. Their preliminary results showed that MDASCA can improve TDCAs and attack the AES implemented with a compact lookup table of 256 bytes. This paper performs a comprehensive study of MDASCA-based TDCAs (MDATDCA) on most of the AES implementations that are widely used. First, the key recovery in TDCA is depicted by an abstract model regardless of the specific attack techniques. Then, the previous work of TDCAs on AES is classified into three types and its limitations are analyzed. How to utilize the cache events with MDATDCA is presented and the overhead is also calculated. To evaluate MDATDCA on AES, this paper constructs a mathematical model to estimate the maximal number of leakage rounds that can be utilized and the minimal number of cache traces required for a successful MDATDCA. Extensive experiments are conducted under different implementations, attack scenarios and key lengths of AES. The experimental results are consistent with the theoretical analysis. Many improvements are achieved. For the first time, we show that TDCAs on AES-192 and AES-256 become possible with the MDATDCA technique. Our work attests that combining TDCAs with algebraic techniques is a very efficient way to improve cache attacks.

Eurasian jays, Garrulus glandarius, flexibly switch caching and pilfering tactics in response to social context

Corvids such as jays and ravens cache food for future consumption and can remember the location of caches that they have seen others make. Given the risk of caches being pilfered by observers, corvids limit opportunities for conspecifics to witness caching events. Faced with cache protection tactics, pilferers should also utilize tactics to maximize their success. Cacher–pilferer interactions and their underlying cognition have largely been investigated in semisocial ravens, Corvus corax, and western scrub-jays, Aphelocoma californica. However to understand the factors influencing the development of these abilities, data are required from species that differ in their socioecology from ravens and western scrub-jays. In the current study, we tested the caching and pilfering behaviour of territorial Eurasian jays in two social contexts. In one context, subjects competed with a dominant conspecific, while in the other the same individuals interacted with a subordinate competitor. When subordinate, birds initially suppressed caching, before caching more in less exposed locations. In contrast, when socially dominant, birds cached more and moved items multiple times. As subordinate pilferers, birds took longer to approach cache sites and approached when the cacher was at a distance, while when dominant, birds rapidly approached the conspecifics’ cache sites, frequently when the cacher was still in the process of caching. Individual jays therefore flexibly switched caching and pilfering tactics in response to the relative dominance of their competitor. We discuss the implications of our results for competing theories on the origin of behavioural flexibility and its underlying complex cognition in the corvid lineage.

Breeding and Foraging Variation of the Plush-Crested Jay (Cyanocorax chrysops) in the Brazilian Atlantic Forest

We monitored six flocks and five active nests of the Plush-crested Jay (Cyanocorax chrysops) at three sites in the Atlantic Forest in southern Brazil. The sites had different vegetation compositions and spanned different levels of anthropogenic disturbance. Home range size in fall/winter was 20–30 ha and the breeding territory size in spring/summer was 5–10 ha in size. Territories were smaller across sites with higher anthropogenic food supplementation. Flock sizes were 5–11 individuals during spring/summer and 8–15 individuals during fall/winter. The Plush-crested Jay is a cooperative breeder, nests were 4–7 m above ground level, the incubation period was 18-20 days, brood size (x¯ ± SD) was 3.4 ± 0.80 eggs per nest, and nestlings fledged 23 ± 1.26 days after hatching. This species occupies all forest strata but tends to use the understory and middle levels most (G = 178.2; P < 0.01). Invertebrates were the most frequently consumed item in all areas, but percent consumption varied among sites (G = 105.06; P < 0.01). We observed 110 food caching events throughout the year, primarily seeds of Araucaria angustifolia, maize, and coconuts. Caches were on the ground (n = 40), in epiphytes (n = 47), and on branches (n = 23). Levels of anthropogenic food supplementation resulted in variation in territory and home-range size, nestling survival rates, strata occupation, and diet composition of the Plush-crested Jay.

Demand-driven software race detection using hardware performance counters

Dynamic data race detectors are an important mechanism for creating robust parallel programs. Software race detectors instrument the program under test, observe each memory access, and watch for inter-thread data sharing that could lead to concurrency errors. While this method of bug hunting can find races that are normally difficult to observe, it also suffers from high runtime overheads. It is not uncommon for commercial race detectors to experience 300x slowdowns, limiting their usage. This paper presents a hardware-assisted demand-driven race detector. We are able to observe cache events that are indicative of data sharing between threads by taking advantage of hardware available on modern commercial microprocessors. We use these to build a race detector that is only enabled when it is likely that inter-thread data sharing is occurring. When little sharing takes place, this demand-driven analysis is much faster than contemporary continuous-analysis tools without a large loss of detection accuracy. We modified the race detector in Intel(R) Inspector XE to utilize our hardware-based sharing indicator and were able to achieve performance increases of 3x and 10x in two parallel benchmark suites and 51x for one particular program.

Knower–guesser differentiation in ravens: others' viewpoints matter

Differentiating between individuals with different knowledge states is an important step in child development and has been considered as a hallmark in human evolution. Recently, primates and corvids have been reported to pass knower-guesser tasks, raising the possibility of mental attribution skills in non-human animals. Yet, it has been difficult to distinguish 'mind-reading' from behaviour-reading alternatives, specifically the use of behavioural cues and/or the application of associatively learned rules. Here, I show that ravens (Corvus corax) observing an experimenter hiding food are capable of predicting the behaviour of bystanders that had been visible at both, none or just one of two caching events. Manipulating the competitors' visual field independently of the view of the test-subject resulted in an instant drop in performance, whereas controls for behavioural cues had no such effect. These findings indicate that ravens not only remember whom they have seen at caching but also take into account that the other's view was blocked. Notably, it does not suffice for the birds to associate specific competitors with specific caches. These results support the idea that certain socio-ecological conditions may select for similar cognitive abilities in distantly related species and that some birds have evolved analogous precursors to a human theory-of-mind.

Western scrub-jays conceal auditory information when competitors can hear but cannot see

Western scrub-jays (Aphelocoma californica) engage in a variety of cache-protection strategies to reduce the chances of cache theft by conspecifics. Many of these strategies revolve around reducing visual information to potential thieves. This study aimed to determine whether the jays also reduce auditory information during caching. Each jay was given the opportunity to cache food in two trays, one of which was filled with small pebbles that made considerable noise when cached in ('noisy' tray), whereas the other one contained soil that made little detectable noise when cached in ('quiet' tray). When the jays could be heard, but not seen, by a competitor, they cached proportionally less food items in the 'noisy' substrate than when they cached alone in the room, or when they could be seen and heard by competitors. These results suggest that western scrub-jays know when to conceal auditory information, namely when a competitor cannot see but can hear the caching event.

ECMon

The advent of multicores has introduced new challenges for programmers to provide increased performance and software reliability. There has been significant interest in techniques that use software speculation to better utilize the computational power of multicores. At the same time, several recent proposals for ensuring software reliability are not applicable in a multicore setting due to their inability to handle interprocessor shared memory dependences (ISMDs). The demands for performing speculation and ensuring software reliability in a multicore setting, although seemingly different, share a common requirement: the need for monitoring program execution and collecting interprocessor dependence information at low overhead. For example, an important component of speculation is the effcient detection of missspeculation which in turn requires dependence information. Likewise, tasks that help ensure software reliability on multicores, including recording for replay , require ISMD information. In this paper, we propose ECMon: support for exposing cache events to the software. This enables the programmer to catch these events and react to them; in effect, efficiently exposing the ISMDs to the programmer. In the context of speculation, we show how ECMon optimizes the detection of miss-speculation; we use this simple support to speculate past active barriers and achieve a speedup of 12% for the set of parallel programs considered. As an application of ensuring software reliability, we show how ECMon can be used to record shared memory dependences on multicores using no specialized hardware support at only 2.8 fold execution time overhead.

Runtime monitoring on multicores via OASES

Runtime monitoring support serves as a foundation for the important tasks of providing security, performing debugging, and improving performance of applications. Often runtime monitoring requires the maintenance of information associated with each of the application's original memory location, which is held in corresponding shadow memory locations. Unfortunately, existing robust shadow memory implementations are inefficient. In this paper, we present OASES: OS and Architectural Support for Efficient Shadow memory implementation for multicores that is also robust. A combination of operating system support (in the form of coupled allocation of memory pages used by the application and associated shadow memory pages) and architectural support (in the form of ISA support and exposed cache events) is proposed. Our page allocation policy enables fast translation of original addresses into corresponding shadow memory addresses; thus allowing implicit addressing of shadow memory. By exposing the cache events to the software, we ensure in software that the shadow memory instructions execute atomically with their corresponding original memory instructions. Our experiments show that the overheads of runtime monitoring tasks are significantly reduced in comparison to previous software implementations.