A review of recurrent neural network based camera localization for indoor environments
Camera localization involves the estimation of the camera pose of an image from a random
scene. We used a single image or sequence of images or videos as the input. The output …
scene. We used a single image or sequence of images or videos as the input. The output …
A hierarchical neural model of data prefetching
This paper presents Voyager, a novel neural network for data prefetching. Unlike previous
neural models for prefetching, which are limited to learning delta correlations, our model can …
neural models for prefetching, which are limited to learning delta correlations, our model can …
TinyBERT for branch prediction in modern microprocessors
A Alajmi, B AlSarraf, Z Abualhassan, AA Fairouz… - Neural Computing and …, 2024 - Springer
Recent progress has highlighted the crucial importance of branch prediction (BP) in
optimizing computer performance, especially in reducing computational delays by …
optimizing computer performance, especially in reducing computational delays by …
Whisper: Profile-guided branch misprediction elimination for data center applications
Modern data center applications experience frequent branch mispredictions–degrading
performance, increasing cost, and reducing energy efficiency in data centers. Even the state …
performance, increasing cost, and reducing energy efficiency in data centers. Even the state …
Branch runahead: An alternative to branch prediction for impossible to predict branches
S Pruett, Y Patt - MICRO-54: 54th Annual IEEE/ACM International …, 2021 - dl.acm.org
High performance microprocessors require high levels of instruction supply. Branch
prediction has been the most important driver of this for nearly 30 years. Unfortunately …
prediction has been the most important driver of this for nearly 30 years. Unfortunately …
A New Formulation of Neural Data Prefetching
Temporal data prefetchers have the potential to produce significant performance gains by
prefetching irregular data streams. Recent work has introduced a neural model for temporal …
prefetching irregular data streams. Recent work has introduced a neural model for temporal …
Ocolos: Online code layout optimizations
The processor front-end has become an increasingly important bottleneck in recent years
due to growing application code footprints, particularly in data centers. First-level instruction …
due to growing application code footprints, particularly in data centers. First-level instruction …
Effective Context-Sensitive Memory Dependence Prediction
SS Kim, A Ros - 2024 IEEE International Symposium on High …, 2024 - ieeexplore.ieee.org
Memory dependence prediction is a fundamental technique to increase instruction-and
memory-level parallelism in out-of-order processors, which are crucial for high performance …
memory-level parallelism in out-of-order processors, which are crucial for high performance …
Cost-Effective RF Fingerprinting Based on Hybrid CVNN-RF Classifier with Automated Multi-Dimensional Early-Exit Strategy
J Gan, Z Du, Q Li, H Shao, J Lin, Y Pan… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
While the Internet of Things (IoT) technology is booming and offers huge opportunities for
information exchange, it also faces unprecedented security challenges. As an important …
information exchange, it also faces unprecedented security challenges. As an important …
Branch prediction as a reinforcement learning problem: Why, how and case studies
Recent years have seen stagnating improvements to branch predictor (BP) efficacy and a
dearth of fresh ideas in branch predictor design, calling for fresh thinking in this area. This …
dearth of fresh ideas in branch predictor design, calling for fresh thinking in this area. This …