23 research outputs found
High Performance Computing using Infiniband-based clusters
L'abstract è presente nell'allegato / the abstract is in the attachmen
E-commerce bot traffic: in-network impact, detection, and mitigation
In-network caching expedites data retrieval by storing frequently accessed data items within programmable data planes, thereby reducing data access latency. In this paper we explore a vulnerability of in-network caching to bots’ traffic, showing it can significantly degrade performance. As bots constitute up to 70% of traffic on e-commerce platforms like Amazon, this is a critical problem. To mitigate the effect of bots’ traffic
we introduce In-network Caching Shelter (INCS), an in-network machine learning solution implemented on NVIDIA BlueField-2 DPU. Our evaluation shows that INCS can detect malicious bot traffic patterns with accuracy up to 94.72%. Furthermore, INCS takes smart actions to mitigate the effects of bot activity
Analysis and optimization of synchronization algorithms for multicore architectures
Multicore design is a major issue in modern computer architectures. Programmers are urged to design innovative algorithms by exploiting multicore facilities. Since synchronization affects the performance of multithread algorithms, the selection of an effective synchronization mechanism is critical for multicore environments. Modern computers provide special hardware instructions that allow to atomically read and modify the content of a word (e.g., the cmpxchg instruction in Intel x86 CPUs), so they can be used for synchronization of threads. Moreover, software techniques can synchronize threads without any dependency on hardware instructions. This study considers the main synchronization techniques, such as Ticket lock, which guarantees fairness execution to all threads, Filter lock, which is intended for multiple threads, Readers-writer lock, which aims to solve the readers-writers problem and Read-Copy Update (RCU), which reduces the overhead in readers-writer lock. The first contribution of this study is to evaluate the costs of the mentioned synchronization techniques, due for example to memory access, system call, and spinning, i.e., the act of querying (or in some cases modifying) an object in memory and waiting for its content. In order to reduce the costs of the mentioned synchronization mechanisms, state-of-the-art approaches exploit hardware or software techniques. The second contribution of this study is the analysis of both hardware and software solutions to reduce the synchronization costs. Moreover, a comparative study to highlight benefits and drawbacks of the different synchronization mechanisms has been performed.
Different software solutions such as backoff, a waiting time to reduce the bus traffic, non blocking algorithm, a synchronization mechanism without blocking primitives, and compiler barrier, a compiler directive to avoid reordering of the instructions, are well-known techniques which are investigated in this study. Beside software solutions, hardware manufacturers introduce various facilities in shared memory or distributed environment to enhance the performance of synchronization mechanisms. Examples of hardware solutions are hardware message passing and different layer of caches in the shared memory environment, and Remote Direct Memory Access (RDMA) in distributed environment. Experimental benchmarks have been executed on a node of cluster (Opteron 6276 2.3 GHz CPU with 16 cores and running CentOS 6.3 Operating System2). The experiments, which are intended to represent a useful aid for researchers and practitioners interested in optimization of parallel algorithms, show that:
1. The update rate directly impacts on performance, even if a non blocking algorithm is exploited.
2. The cost of keeping data locality should not exceed the cost of cache misses.
3. Exploiting a non blocking synchronization algorithm (i.e., RCU) leads to a better performance.
4. Critical section length should be reduced as much as possible in order to increase the performance.
5. In order to reduce the bus traffic, it is better to avoid spinning.
6. Hardware message passing can increase the performance of shared memory synchronization model.
7. Synchronization methods with heavy instructions should be avoided
A Review on Fall Prediction and Prevention System for Personal Devices: Evaluation and Experimental Results
Injuries due to unintentional falls cause high social cost in which several systems have been developed to reduce them. Recently, two trends can be recognized. Firstly, the market is dominated by fall detection systems, which activate an alarm after a fall occurrence, but the focus is moving towards predicting and preventing a fall, as it is the most promising approach to avoid a fall injury. Secondly, personal devices, such as smartphones, are being exploited for implementing fall systems, because they are commonly carried by the user most of the day. This paper reviews various fall prediction and prevention systems, with a particular interest to the ones that can rely on the sensors embedded in a smartphone, i.e., accelerometer and gyroscope. Kinematic features obtained from the data collected from accelerometer and gyroscope have been evaluated in combination with different machine learning algorithms. An experimental analysis compares the evaluated approaches by evaluating their accuracy and ability to predict and prevent a fall. Results show that tilt features in combination with a decision tree algorithm present the best performance
Analysis and optimization of synchronization algorithms for multicore architectures
Multicore design is a major issue in modern computer architectures. Programmers are urged to design innovative algorithms by exploiting multicore facilities. Since synchronization affects the performance of multithread algorithms, the selection of an effective synchronization mechanism is critical for multicore environments. Modern computers provide special hardware instructions that allow to atomically read and modify the content of a word (e.g., the cmpxchg instruction in Intel x86 CPUs), so they can be used for synchronization of threads. Moreover, software techniques can synchronize threads without any dependency on hardware instructions. This study considers the main synchronization techniques, such as Ticket lock, which guarantees fairness execution to all threads, Filter lock, which is intended for multiple threads, Readers-writer lock, which aims to solve the readers-writers problem and Read-Copy Update (RCU), which reduces the overhead in readers-writer lock. The first contribution of this study is to evaluate the costs of the mentioned synchronization techniques, due for example to memory access, system call, and spinning, i.e., the act of querying (or in some cases modifying) an object in memory and waiting for its content. In order to reduce the costs of the mentioned synchronization mechanisms, state-of-the-art approaches exploit hardware or software techniques. The second contribution of this study is the analysis of both hardware and software solutions to reduce the synchronization costs. Moreover, a comparative study to highlight benefits and drawbacks of the different synchronization mechanisms has been performed.
Different software solutions such as backoff, a waiting time to reduce the bus traffic, non blocking algorithm, a synchronization mechanism without blocking primitives, and compiler barrier, a compiler directive to avoid reordering of the instructions, are well-known techniques which are investigated in this study. Beside software solutions, hardware manufacturers introduce various facilities in shared memory or distributed environment to enhance the performance of synchronization mechanisms. Examples of hardware solutions are hardware message passing and different layer of caches in the shared memory environment, and Remote Direct Memory Access (RDMA) in distributed environment. Experimental benchmarks have been executed on a node of cluster (Opteron 6276 2.3 GHz CPU with 16 cores and running CentOS 6.3 Operating System2). The experiments, which are intended to represent a useful aid for researchers and practitioners interested in optimization of parallel algorithms, show that:
1. The update rate directly impacts on performance, even if a non blocking algorithm is exploited.
2. The cost of keeping data locality should not exceed the cost of cache misses.
3. Exploiting a non blocking synchronization algorithm (i.e., RCU) leads to a better performance.
4. Critical section length should be reduced as much as possible in order to increase the performance.
5. In order to reduce the bus traffic, it is better to avoid spinning.
6. Hardware message passing can increase the performance of shared memory synchronization model.
7. Synchronization methods with heavy instructions should be avoided
Nonlinear predictive threshold model for real-time abnormal gait detection
Falls are critical events for human health due to the associated risk of physical and psychological injuries. Several fall related systems have been developed in order to reduce injuries. Among them, fall-risk prediction systems are one of the most promising approaches, as they strive to predict a fall before its occurrence. A category of fall-risk prediction systems evaluates balance and muscle strength through some clinical functional assessment tests, while other prediction systems investigate the recognition of abnormal gait patterns to predict a fall in real-time. The main contribution of this paper is a nonlinear model of user gait in combination with a threshold-based classification in order to recognize abnormal gait patterns with low complexity and high accuracy. In addition, a dataset with realistic parameters is prepared to simulate abnormal walks and to evaluate fall prediction methods. The accelerometer and gyroscope sensors available in a smartphone have been exploited to create the dataset. The proposed approach has been implemented and compared with the state-of-the-art approaches showing that it is able to predict an abnormal walk with a higher accuracy (93.5%) and a higher efficiency (up to 3.5 faster) than other feasible approaches
GridWatch: a smart network for smart grid
The adoption of decentralized energy market models
facilitates the exchange of surplus power among local nodes in
peer-to-peer settings. However, decentralized energy transactions
within untrusted and non-transparent energy markets in modern
Smart Grids expose vulnerabilities and are susceptible to attacks.
One such attack is the False Data Injection Attack, where malicious entities intentionally inject misleading information into the
system. To address this threat, this paper proposes GridWatch,
an effective real-time in-network intelligent framework to detect
false data injection attacks. Gridwatch operates in a hybrid
model. It deploys inference model in the programmable network
devices and also on the server to detect false data injection
attacks. GridWatch was evaluated using a real-world dataset
from Austin, Texas, and can detect false data injection attacks
with 94.8% accuracy. GridWatch on average performs 4 billions
transactions per second in less than 1.8 microsecond latency
Internet of Things for fall prediction and prevention
Internet of Things (IoT) is making a breakthrough for the development of innovative healthcare systems. IoT-based health applications are expected to change the paradigm traditionally followed by physicians for diagnosis, by moving health monitoring from the clinical environment to the domestic space. Fall avoidance is a field where the continuous monitoring allowed by the IoT-based framework offers tremendous benefits to the user. In fact, falls are highly damaging due to both physical and psychological injuries. Currently, the most promising approaches to reduce fall injuries are fall prediction, which strives to predict a fall before its occurrence, and fall prevention, which assesses balance and muscle strength through some clinical functional tests. In this context, the IoT-based framework provides real-time emergency notification as soon as fall is predicted, mid-term analysis on the monitored activities, and data logging for long-term analysis by clinical experts. This approach gives more information to experts for estimating the risk of a future fall and for suggesting proper exercises
Communicating Efficiently on Cluster-Based Remote Direct Memory Access (RDMA) over InfiniBand Protocol
Distributed systems are commonly built under the assumption that the network is the primary bottleneck, however this assumption no longer holds by emerging high-performance RDMA enabled protocols in datacenters. Designing distributed applications over such protocols requires a fundamental rethinking in communication components in comparison with traditional protocols (i.e., TCP/IP). In this paper, communication paradigms in existing systems and new possible paradigms have been investigated. Advantages and drawbacks of each paradigm have been comprehensively analyzed and experimentally evaluated. The experimental results show that writing the requests to server and reading the response presents up to 10 times better performance comparing to other communication paradigms. To further expand the investigation, the proposed communication paradigm has been substituted in a real-world distributed application, and the performance has been enhanced up to seven times