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To satisfy the growing throughput demand of data-intensive applications, the performance of optical communication systems increased dramatically in recent years. With higher throughput, more advanced equalizers are crucial, to compensate…
The traditional USB 3.0 communication based on FPGA uses an external chip as a USB PHY or a USB controller including a USB PHY. This paper realizes a USB 3.0 controller by using FPGA resources, in which FPGA logic realizes a serial…
Convolutional neural networks (CNNs) have been widely employed in many applications such as image classification, video analysis and speech recognition. Being compute-intensive, CNN computations are mainly accelerated by GPUs with high…
One of the challenges in the wireless sensor applications which are gaining much attention is the real-time transmission of continuous data packets across the network. Though advances in communication in sensor networks are providing…
Packet classification is a vital and complicated task as the processing of packets should be done at a specified line speed. In order to classify a packet as belonging to a particular flow or set of flows, network nodes must perform a…
Due to the increasing heterogeneity in network user requirements, dynamically varying day to day network traffic patterns and delay in-network service deployment, there is a huge demand for scalability and flexibility in modern networking…
This paper proposes a PCI Express (PCIE) Wrapper core named PWrapper with FIFO interfaces. Compared with other PCIE solutions, PWrapper has several advantages such as flexibility, isolation of clock domain, etc. PWrapper is implemented and…
Among hardware accelerators for deep-learning inference, data flow implementations offer low latency and high throughput capabilities. In these architectures, each neuron is mapped to a dedicated hardware unit, making them well-suited for…
Embedded systems are parts of our daily life and used in many fields. They can be found in smartphones or in modern cars including GPS, light/rain sensors and other electronic assistance mechanisms. These systems may handle sensitive data…
Improving the efficiency of edge detection in embedded applications, such as UAV control, is critical for reducing system cost and power dissipation. Field programmable gate arrays (FPGA) are a good platform for making improvements because…
The deployment of the next generation computing platform at ExaFlops scale requires to solve new technological challenges mainly related to the impressive number (up to 10^6) of compute elements required. This impacts on system power…
Hardware specialization is becoming a key enabler of energyefficient performance. Future systems will be increasingly heterogeneous, integrating multiple specialized and programmable accelerators, each with different memory demands.…
Modern data analytics requires a huge amount of computing power and processes a massive amount of data. At the same time, the underlying computing platform is becoming much more heterogeneous on both hardware and software. Even though…
In data communication via internet, security is becoming one of the most influential aspects. One way to support it is by classifying and filtering ethernet packets within network devices. Packet classification is a fundamental task for…
Supercomputers getting ever larger and energy-efficient is at odds with the reliability of the used hardware. Thus, the time intervals between component failures are decreasing. Contrarily, the latencies for individual operations of…
We implemented the NaNet FPGA-based PCI2 Gen2 GbE/APElink NIC, featuring GPUDirect RDMA capabilities and UDP protocol management offloading. NaNet is able to receive a UDP input data stream from its GbE interface and redirect it, without…
Data breaches and cyberattacks represent a severe problem in higher education institutions and universities that can result in illegal access to sensitive information and data loss. To enhance the security of data transmission, Intrusion…
Deep networks are frequently tuned to novel tasks and continue learning from ongoing data streams. Such sequential training requires consolidation of new and past information, a challenge predominantly addressed by retaining the most…
Embedded system performances are bounded by power consumption. The trend is to offload greedy computations on hardware accelerators as GPU, Xeon Phi or FPGA. FPGA chips combine both flexibility of programmable chips and energy-efficiency of…
With the rapidly-developing high-speed wireless communications, the 60 GHz millimeter-wave frequency range and radio-over-fiber systems have been investigated as a promising solution to deliver mm-wave signals. Neural networks have been…