Related papers: Performance Considerations for Gigabyte per Second…
Astrophysical radio signals are excellent probes of extreme physical processes that emit them. However, to reach Earth, electromagnetic radiation passes through the ionised interstellar medium (ISM), introducing a frequency-dependent time…
We propose a time-multiplexed DS-DBR/SOA-gated system to deliver low-power fast tuning across S-/C-/L-bands. Sub-ns switching is demonstrated, supporting 122$\times$50 GHz channels over 6.05 THz using AI techniques.
Convolutional Neural Networks are extensively used in a wide range of applications, commonly including computer vision tasks like image and video classification, recognition, and segmentation. Recent research results demonstrate that…
Large scientific collaborations often share huge volumes of data around the world. Consequently a significant amount of network bandwidth is needed for data replication and data access. Users in the same region may possibly share resources…
Creating geometric digital twins (gDT) for as-built roads still faces many challenges, such as low automation level and accuracy, limited asset types and shapes, and reliance on engineering experience. A novel scan-to-building information…
With the rapid development of network protocol, TCP/IP has been widely applied in various OS systems because of its advantages of high-speed network transmission and standardization. Furthermore, TCP/IP has the functions of retransmission…
The design of mission scenarios for the flyby investigation of nearby star systems by probes launched using directed energy is addressed. Multiple probes are launched with a fixed launch infrastructure, and download of scientific data…
Gi-Fi stands for Gigabit Wireless. Gi-Fi is a wireless transmission system which is ten times faster than other technology and its chip delivers short-range multigigabit data transfer in a local environment. Gi-Fi is a wireless technology…
K-nearest neighbor search is one of the fundamental tasks in various applications and the hierarchical navigable small world (HNSW) has recently drawn attention in large-scale cloud services, as it easily scales up the database while…
We present our experiences using cloud computing to support data-intensive analytics on satellite imagery for commercial applications. Drawing from our background in high-performance computing, we draw parallels between the early days of…
Modern Graphics Processing Units (GPUs) are now considered accelerators for general purpose computation. A tight interaction between the GPU and the interconnection network is the strategy to express the full potential on capability…
The potential application of advanced digital communication schemes in a future upgrade of the CMS Tracker readout optical links is currently being investigated at CERN. We show experimentally that multi-Gbit/s data rates are possible over…
Following the scale-up of new radio (NR) complexity in 5G and beyond, the physical layer's computing load on base stations is increasing under a strictly constrained latency and power budget; base stations must process > 20-Gb/s uplink…
Convolutional neural network (CNN) offers significant accuracy in image detection. To implement image detection using CNN in the internet of things (IoT) devices, a streaming hardware accelerator is proposed. The proposed accelerator…
In principle, a network can transfer data at nearly the speed of light. Today's Internet, however, is much slower: our measurements show that latencies are typically more than one, and often more than two orders of magnitude larger than the…
Incoherent dedispersion is a computationally intensive problem that appears frequently in pulsar and transient astronomy. For current and future transient pipelines, dedispersion can dominate the total execution time, meaning its…
The upcoming Square Kilometer Array (SKA) is expected to produce humongous amount of data for undertaking H{\sc i}~science. We have developed an MPI-based {\sc Python} pipeline to deal with the large data efficiently with the present…
Interplanetary networks (IPNs) present unique challenges such as extreme delay, high loss, and frequent disruptions that severely degrade the performance of conventional transport protocols like Transmission Control Protocol (TCP) and Quick…
We live in a data-centric world where we are heading to generate close to 200 Zettabytes of data by the year 2025. Our data processing requirements have also increased as we push to build data processing frameworks that can process large…
Modern GPUs are equipped with tensor cores (TCs) that are commonly used for matrix multiplication in artificial intelligence workloads. However, because they have high computational throughput, they can lead to significant performance gains…