Fakernet -- small and fast FPGA-based TCP and UDP communication
March 27, 2020 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
H. T. Johansson, A. Furufors, P. Klenze
arXiv ID
2003.12527
Category
physics.ins-det
Cross-listed
cs.NI
Citations
2
Venue
arXiv.org
Last Checked
3 months ago
Abstract
A common theme of data acquisition systems is the transport of data from digitising front-end modules to stable storage and online analysis. A good choice today is to base this on the ubiquitous, commercially and cheaply available Ethernet technology. A firmware building block to turn already the FPGA of front-end electronics into a TCP data source and UDP control interface using a data-flow architecture is presented. The overall performance targets are to be able to saturate a 1 Gbps network link with outbound data, while using few FPGA resources. The goal is to replace the use of custom data buses and protocols with ordinary Ethernet equipment. These objectives are achieved by being just-enough conforming, such that no special drivers are needed in the PC equipment interfacing with the here presented Fakernet system. An important design choice is to handle all packet-data internally as 16-bit words, thus reducing the clock-speed requirements. An advantageous circumstance is that even at 1 Gbps speeds, for local network segments, the round-trip times are usually well below 500 microseconds. Thus, less than 50 kiB of unacknowledged data needs to be in-flight, allowing to saturate a network link without TCP window scaling. The Fakernet system has so far been shown to saturate a 100 Mbps link at 11.7 MB/s of TCP output data, and able to do 32-bit control register accesses at over 450 kword/s.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ physics.ins-det
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics
R.I.P.
๐ป
Ghosted
Highly curved image sensors: a practical approach for improved optical performance
R.I.P.
๐ป
Ghosted
Using LSTM recurrent neural networks for monitoring the LHC superconducting magnets
R.I.P.
๐ป
Ghosted
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs
R.I.P.
๐ป
Ghosted
A Computational Model of a Single-Photon Avalanche Diode Sensor for Transient Imaging
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted