Ariel Waizel discusses the Data Plane Development Kit (DPDK), an API for developing fast packet processing code in user space.
* Who needs this library? Why bypass the kernel?
* How does it work?
* How good is it? What are the benchmarks?
* Pros and cons
Ariel worked on kernel development at the IDF, Ben Gurion University, and several companies. He is interested in networking, security, machine learning, and basically everything except UI development. Currently a Solution Architect at ConteXtream (an HPE company), which specializes in SDN solutions for the telecom industry.
Ariel Waizel discusses the Data Plane Development Kit (DPDK), an API for developing fast packet processing code in user space.
* Who needs this library? Why bypass the kernel?
* How does it work?
* How good is it? What are the benchmarks?
* Pros and cons
Ariel worked on kernel development at the IDF, Ben Gurion University, and several companies. He is interested in networking, security, machine learning, and basically everything except UI development. Currently a Solution Architect at ConteXtream (an HPE company), which specializes in SDN solutions for the telecom industry.
This presentation introduces Data Plane Development Kit overview and basics. It is a part of a Network Programming Series.
First, the presentation focuses on the network performance challenges on the modern systems by comparing modern CPUs with modern 10 Gbps ethernet links. Then it touches memory hierarchy and kernel bottlenecks.
The following part explains the main DPDK techniques, like polling, bursts, hugepages and multicore processing.
DPDK overview explains how is the DPDK application is being initialized and run, touches lockless queues (rte_ring), memory pools (rte_mempool), memory buffers (rte_mbuf), hashes (rte_hash), cuckoo hashing, longest prefix match library (rte_lpm), poll mode drivers (PMDs) and kernel NIC interface (KNI).
At the end, there are few DPDK performance tips.
Tags: access time, burst, cache, dpdk, driver, ethernet, hub, hugepage, ip, kernel, lcore, linux, memory, pmd, polling, rss, softswitch, switch, userspace, xeon
SOSCON 2019.10.17
What are the methods for packet processing on Linux? And how fast are each packet processing methods? In this presentation, we will learn how to handle packets on Linux (User space, socket filter, netfilter, tc), and compare performance with analysis of where each packet processing is done in the network stack (hook point). Also, we will discuss packet processing using XDP, an in-kernel fast-path recently added to the Linux kernel. eXpress Data Path (XDP) is a high-performance programmable network data-path within the Linux kernel. The XDP is located at the lowest level of access through SW in the network stack, the point at which driver receives the packet. By using the eBPF infrastructure at this hook point, the network stack can be expanded without modifying the kernel.
Daniel T. Lee (Hoyeon Lee)
@danieltimlee
Daniel T. Lee currently works as Software Engineer at Kosslab and contributing to Linux kernel BPF project. He has interest in cloud, Linux networking, and tracing technologies, and likes to analyze the kernel's internal using BPF technology.
High-Performance Networking Using eBPF, XDP, and io_uringScyllaDB
In the networking world there are a number of ways to increase performance over naive use of basic Berkeley sockets. These techniques have ranged from polling blocking sockets, non-blocking sockets controlled by Epoll, all the way through completely bypassing the Linux kernel for maximum network performance where you talk directly to the network interface card by using something like DPDK or Netmap. All these tools have their place, and generally occupy a space from convenience to performance. But in recent years, that landscape has changed massively.. The tools available to the average Linux systems developer have improved from the creation of io_uring, to the expansion of bpf from a simple filtering language to a full-on programming environment embedded directly in the kernel. Along with that came something called XDP (express datapath). This was Linux kernel's answer to kernel-bypass networking. AF_XDP is the new socket type created by this feature, and generally works very similarly to something like DPDK. History lessons out of the way, this talk will look into, and discuss the merits of this technology, it's place in the broader ecosystem and how it can be used to attain the highest level of performance possible. This talk will dive into crucial details, such as how AF_XDP works, how it can be integrated into a larger system and finally more advanced topics such as request sharding/load balancing. There will be detailed look at the design of AF_XDP, the eBpf code used, as well as the userspace code required to drive it all. It will also include performance numbers from this setup compared to regular kernel networking. And most importantly how to put all this together to handle as much data as possible on a single modern multi-core system.
Cilium - Container Networking with BPF & XDPThomas Graf
This talk demonstrates that programmability and performance does not require user space networking, it can be achieved in the kernel by generating BPF programs and leveraging the existing kernel subsystems. We will demo an early prototype which provides fast IPv6 & IPv4 connectivity to containers, container labels based security policy with avg cost O(1), and debugging and monitoring based on the per-cpu perf ring buffer. We encourage a lively discussion on the approach taken and next steps.
This presentation introduces Data Plane Development Kit overview and basics. It is a part of a Network Programming Series.
First, the presentation focuses on the network performance challenges on the modern systems by comparing modern CPUs with modern 10 Gbps ethernet links. Then it touches memory hierarchy and kernel bottlenecks.
The following part explains the main DPDK techniques, like polling, bursts, hugepages and multicore processing.
DPDK overview explains how is the DPDK application is being initialized and run, touches lockless queues (rte_ring), memory pools (rte_mempool), memory buffers (rte_mbuf), hashes (rte_hash), cuckoo hashing, longest prefix match library (rte_lpm), poll mode drivers (PMDs) and kernel NIC interface (KNI).
At the end, there are few DPDK performance tips.
Tags: access time, burst, cache, dpdk, driver, ethernet, hub, hugepage, ip, kernel, lcore, linux, memory, pmd, polling, rss, softswitch, switch, userspace, xeon
SOSCON 2019.10.17
What are the methods for packet processing on Linux? And how fast are each packet processing methods? In this presentation, we will learn how to handle packets on Linux (User space, socket filter, netfilter, tc), and compare performance with analysis of where each packet processing is done in the network stack (hook point). Also, we will discuss packet processing using XDP, an in-kernel fast-path recently added to the Linux kernel. eXpress Data Path (XDP) is a high-performance programmable network data-path within the Linux kernel. The XDP is located at the lowest level of access through SW in the network stack, the point at which driver receives the packet. By using the eBPF infrastructure at this hook point, the network stack can be expanded without modifying the kernel.
Daniel T. Lee (Hoyeon Lee)
@danieltimlee
Daniel T. Lee currently works as Software Engineer at Kosslab and contributing to Linux kernel BPF project. He has interest in cloud, Linux networking, and tracing technologies, and likes to analyze the kernel's internal using BPF technology.
High-Performance Networking Using eBPF, XDP, and io_uringScyllaDB
In the networking world there are a number of ways to increase performance over naive use of basic Berkeley sockets. These techniques have ranged from polling blocking sockets, non-blocking sockets controlled by Epoll, all the way through completely bypassing the Linux kernel for maximum network performance where you talk directly to the network interface card by using something like DPDK or Netmap. All these tools have their place, and generally occupy a space from convenience to performance. But in recent years, that landscape has changed massively.. The tools available to the average Linux systems developer have improved from the creation of io_uring, to the expansion of bpf from a simple filtering language to a full-on programming environment embedded directly in the kernel. Along with that came something called XDP (express datapath). This was Linux kernel's answer to kernel-bypass networking. AF_XDP is the new socket type created by this feature, and generally works very similarly to something like DPDK. History lessons out of the way, this talk will look into, and discuss the merits of this technology, it's place in the broader ecosystem and how it can be used to attain the highest level of performance possible. This talk will dive into crucial details, such as how AF_XDP works, how it can be integrated into a larger system and finally more advanced topics such as request sharding/load balancing. There will be detailed look at the design of AF_XDP, the eBpf code used, as well as the userspace code required to drive it all. It will also include performance numbers from this setup compared to regular kernel networking. And most importantly how to put all this together to handle as much data as possible on a single modern multi-core system.
Cilium - Container Networking with BPF & XDPThomas Graf
This talk demonstrates that programmability and performance does not require user space networking, it can be achieved in the kernel by generating BPF programs and leveraging the existing kernel subsystems. We will demo an early prototype which provides fast IPv6 & IPv4 connectivity to containers, container labels based security policy with avg cost O(1), and debugging and monitoring based on the per-cpu perf ring buffer. We encourage a lively discussion on the approach taken and next steps.
In Network Computing Prototype Using P4 at KSC/KREONET 2019Kentaro Ebisawa
Case Study of P4 applying to CAN (Control Area Network) data pre-processing using FPGA + Netcope P4 compiler.
Presented at KSC / KREONET WORKSHOP 2019 | DAY 1 Session 1: SDN/NFV/P4
http://www.ksc2019.re.kr/
Comparison of SRv6 Extensions uSID, SRv6+, C-SRHKentaro Ebisawa
Comparing concept, SID and header format of compressed Segment Routing IPv6 proposals such as uSID, SRv6+, C-SRH. Slide presented at SRv6 Consortium @Tokyo on 23rd Aug 2019.
"p4srv6 (P4-16) design document rev1.0" Overview of Open Source SRv6 Mobile Userplane P4-16 on BMv2 design (planned to be public in March) #enog #enog55 @Nigata http://enog.jp/archives/2014
SRv6 Mobile User Plane : Initial POC and ImplementationKentaro Ebisawa
SRv6 Mobile Uplane POC results and findings talked at ENOG55 @Nigata http://enog.jp/archives/2014
SRv6 functions: T.M.Tmap, End.M.GTP4.E using VPP and P4 on Tofino switch.
JANOG43 Forefront of SRv6, Open Source ImplementationsKentaro Ebisawa
Status of SRv6 Open Source Implementations including where you can find the source code. English slide comes after Japanese.
This is a session from JANOG43 "Forefront of SRv6" program held on 23 Jan 2019 @ Kohu Japan.
https://www.janog.gr.jp/meeting/janog43/program/srv6
* Introduction – Miya Kohno
* SRv6 Update – Clarence Filsfils
* SRv6 Mobile user plane Update – Satoru Matsushima
* SRv6 Open Source Implementation Update – Kentaro Ebisawa
* SRv6 Academy Update – Chunghan Lee
* Vendor Update (Huawei) – Ryuichi Takashima
* Vendor Update (Cisco) – Teppei Kamata
How to build and use GTPing to generate GTP traffic for testing without eNB, SPGW etc. This work was done as part of the preparation of SRv6 mobile user plane POC at SRv6 Consortium, Data plane Study Group, which is a group of people interested in SRv6.
Slides from ONOS/CORD meetup in Tokyo 2018. 20th April 2018.
http://www.e-side.co.jp/onoscordmeetup/#P4_2
Future Mobile User Plane is heavily discussed in many SDOs like 3GPP, IETF etc. and still not concreate. P4 lang is usefull to prototype such changing protocol on software switch and on ASIC/NPU.
This slide introudce one candidate for future Mobile User Plane protocol, SRv6 for Mobile User Plane and proto-type implemented in P4-14.
https://datatracker.ietf.org/doc/draft-ietf-dmm-srv6-mobile-uplane/
Moved to https://speakerdeck.com/ebiken/zebra-srv6-cli-on-linux-dataplane-enog-number-49
Introduction to SRv6, Linux SRv6 implementation and how to add SRv6 CLI to Zebra 2.0 Open Source Network Operation Stack.
Presented at ENOG (Echigo NOG) #49.
“p4alu” is a P4 program who would parse UDP packet with payload in "p4alu header format" and apply calculation.
This program is tested using BMv2 simple_switch P4 target.
zebra is an open source implementation as a successor of GNU Zebra and Quagga project. Together with openconfigd, it will work as data plane agnostic Network Operation Stack working with variable protocol / functional modules.
【DLゼミ】XFeat: Accelerated Features for Lightweight Image Matchingharmonylab
公開URL:https://arxiv.org/pdf/2404.19174
出典:Guilherme Potje, Felipe Cadar, Andre Araujo, Renato Martins, Erickson R. ascimento: XFeat: Accelerated Features for Lightweight Image Matching, Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
概要:リソース効率に優れた特徴点マッチングのための軽量なアーキテクチャ「XFeat(Accelerated Features)」を提案します。手法は、局所的な特徴点の検出、抽出、マッチングのための畳み込みニューラルネットワークの基本的な設計を再検討します。特に、リソースが限られたデバイス向けに迅速かつ堅牢なアルゴリズムが必要とされるため、解像度を可能な限り高く保ちながら、ネットワークのチャネル数を制限します。さらに、スパース下でのマッチングを選択できる設計となっており、ナビゲーションやARなどのアプリケーションに適しています。XFeatは、高速かつ同等以上の精度を実現し、一般的なラップトップのCPU上でリアルタイムで動作します。
セル生産方式におけるロボットの活用には様々な問題があるが,その一つとして 3 体以上の物体の組み立てが挙げられる.一般に,複数物体を同時に組み立てる際は,対象の部品をそれぞれロボットアームまたは治具でそれぞれ独立に保持することで組み立てを遂行すると考えられる.ただし,この方法ではロボットアームや治具を部品数と同じ数だけ必要とし,部品数が多いほどコスト面や設置スペースの関係で無駄が多くなる.この課題に対して音𣷓らは組み立て対象物に働く接触力等の解析により,治具等で固定されていない対象物が組み立て作業中に運動しにくい状態となる条件を求めた.すなわち,環境中の非把持対象物のロバスト性を考慮して,組み立て作業条件を検討している.本研究ではこの方策に基づいて,複数物体の組み立て作業を単腕マニピュレータで実行することを目的とする.このとき,対象物のロバスト性を考慮することで,仮組状態の複数物体を同時に扱う手法を提案する.作業対象としてパイプジョイントの組み立てを挙げ,簡易な道具を用いることで単腕マニピュレータで複数物体を同時に把持できることを示す.さらに,作業成功率の向上のために RGB-D カメラを用いた物体の位置検出に基づくロボット制御及び動作計画を実装する.
This paper discusses assembly operations using a single manipulator and a parallel gripper to simultaneously
grasp multiple objects and hold the group of temporarily assembled objects. Multiple robots and jigs generally operate
assembly tasks by constraining the target objects mechanically or geometrically to prevent them from moving. It is
necessary to analyze the physical interaction between the objects for such constraints to achieve the tasks with a single
gripper. In this paper, we focus on assembling pipe joints as an example and discuss constraining the motion of the
objects. Our demonstration shows that a simple tool can facilitate holding multiple objects with a single gripper.