Adding Token Counting to Directory-Based Cache Coherence

The coherence protocol is a first-order design concern in multicore designs. Directory protocols are naturally scalable, as they place no restrictions on the interconnect and have minimal bandwidth requirements; however, this scalability comes at the cost of increased sharing latency due to indirection. In contrast, broadcast-based systems such as snooping protocols and token coherence reduce latency of sharing misses by sending requests directly to other processors. Unfortunately, their reliance on totally ordered interconnects and/or broadcast limits their scalability. This work introduces PATCH (Predictive/Adaptive Token Counting Hybrid), a coherence protocol that provides the scalability of directory protocols while opportunistically using available bandwidth to reduce sharing latency. PATCH extends a standard directory protocol to track tokens and use token counting rules for enforcing coherence permissions. Token counting allows PATCH to support direct requests on an unordered interconnect, while a novel mechanism called token tenure uses local processor timeouts and the directory’s per-block point of ordering at the home node to guarantee forward progress without relying on broadcast. PATCH makes three main contributions. First, PATCH uses direct request prioritization to match the performance of broadcast-based protocols without restricting scalability. Second, PATCH introduces token tenure, which provides broadcast-free forward progress for token counting protocols. Finally, PATCH provides greater scalability than directory protocols when using inexact encodings of sharers because only processors holding tokens need to acknowledge requests. Overall, PATCH is a “one-size-fits-all” coherence protocol that dynamically adapts to work well for small systems, large systems, and anywhere in betwee

Token Tenure and PATCH: A Predictive/Adaptive Token-Counting Hybrid

Traditional coherence protocols present a set of difficult trade-offs: the reliance of snoopy protocols on broadcast and ordered interconnects limits their scalability, while directory protocols incur a performance penalty on sharing misses due to indirection. This work introduces PATCH (Predictive/Adaptive Token-Counting Hybrid), a coherence protocol that provides the scalability of directory protocols while opportunistically sending direct requests to reduce sharing latency. PATCH extends a standard directory protocol to track tokens and use token-counting rules for enforcing coherence permissions. Token counting allows PATCH to support direct requests on an unordered interconnect, while a mechanism called token tenure provides broadcast-free forward progress using the directory protocol’s per-block point of ordering at the home along with either timeouts at requesters or explicit race notification messages. PATCH makes three main contributions. First, PATCH introduces token tenure, which provides broadcast-free forward progress for token-counting protocols. Second, PATCH deprioritizes best-effort direct requests to match or exceed the performance of directory protocols without restricting scalability. Finally, PATCH provides greater scalability than directory protocols when using inexact encodings of sharers because only processors holding tokens need to acknowledge requests. Overall, PATCH is a “one-size-fits-all” coherence protocol that dynamically adapts to work well for small systems, large systems, and anywhere in between

Security of Electrical, Optical and Wireless On-Chip Interconnects: A Survey

The advancement of manufacturing technologies has enabled the integration of more intellectual property (IP) cores on the same system-on-chip (SoC). Scalable and high throughput on-chip communication architecture has become a vital component in today's SoCs. Diverse technologies such as electrical, wireless, optical, and hybrid are available for on-chip communication with different architectures supporting them. Security of the on-chip communication is crucial because exploiting any vulnerability would be a goldmine for an attacker. In this survey, we provide a comprehensive review of threat models, attacks, and countermeasures over diverse on-chip communication technologies as well as sophisticated architectures.Comment: 41 pages, 24 figures, 4 table

Synesthesia: Detecting Screen Content via Remote Acoustic Side Channels

We show that subtle acoustic noises emanating from within computer screens can be used to detect the content displayed on the screens. This sound can be picked up by ordinary microphones built into webcams or screens, and is inadvertently transmitted to other parties, e.g., during a videoconference call or archived recordings. It can also be recorded by a smartphone or "smart speaker" placed on a desk next to the screen, or from as far as 10 meters away using a parabolic microphone. Empirically demonstrating various attack scenarios, we show how this channel can be used for real-time detection of on-screen text, or users' input into on-screen virtual keyboards. We also demonstrate how an attacker can analyze the audio received during video call (e.g., on Google Hangout) to infer whether the other side is browsing the web in lieu of watching the video call, and which web site is displayed on their screen

Multicast Mobility in Mobile IP Version 6 (MIPv6) : Problem Statement and Brief Survey

Publisher PD

Locality-Adaptive Parallel Hash Joins Using Hardware Transactional Memory

Previous work [1] has claimed that the best performing implementation of in-memory hash joins is based on (radix-)partitioning of the build-side input. Indeed, despite the overhead of partitioning, the benefits from increased cache-locality and synchronization free parallelism in the build-phase outweigh the costs when the input data is randomly ordered. However, many datasets already exhibit significant spatial locality (i.e., non-randomness) due to the way data items enter the database: through periodic ETL or trickle loaded in the form of transactions. In such cases, the first benefit of partitioning — increased locality — is largely irrelevant. In this paper, we demonstrate how hardware transactional memory (HTM) can render the other benefit, freedom from synchronization, irrelevant as well. Specifically, using careful analysis and engineering, we develop an adaptive hash join implementation that outperforms parallel radix-partitioned hash joins as well as sort-merge joins on data with high spatial locality. In addition, we show how, through lightweight (less than 1% overhead) runtime monitoring of the transaction abort rate, our implementation can detect inputs with low spatial locality and dynamically fall back to radix-partitioning of the build-side input. The result is a hash join implementation that is more than 3 times faster than the state-of-the-art on high-locality data and never more than 1% slower