Istio Meetup China Accelerate Service Mesh Network with ebpf Luyao Zhong Istio Meetup China Agenda ● TCP/IP stack overhead in service mesh ● Background knowledge of eBPF ● Independent solution to

#IstioCon Accelerate Istio-CNI with ebpf Xu Yizhou & Guo Ruijing #IstioCon Agenda ● Istio-CNI ● tcp/ip stack overhead between sidecar and service ● Background knowledge of ebpf ● Acceleration for

can elerate’s cblas_?ger and cblas_?axpy func- ed ArmPL function is 1.49⇥ (geomean) faster posed Accelerate implementation (Figure 3). TA Simple Computation Vectors 1 1 1 1 1 1 1 1 1 1 a simple can elerate’s cblas_?ger and cblas_?axpy func- ed ArmPL function is 1.49⇥ (geomean) faster posed Accelerate implementation (Figure 3). TA Simple Computation Vectors Scalar 1 1 1 1 1 1 1 1 1 can elerate’s cblas_?ger and cblas_?axpy func- ed ArmPL function is 1.49⇥ (geomean) faster posed Accelerate implementation (Figure 3). TA Simple Computation Vectors Scalar Accumulate into result 1

//执行绑定的事件 hook1.call(1,2,3) Tapable 的使用-实际例子演示 定义一个 Car 方法，在内部 hooks 上新建钩子。分别是同步钩子 accelerate、 brake（ accelerate 接受一个参数）、异步钩子 calculateRoutes 使用钩子对应的绑定和执行方法 calculateRoutes 使用 tapPromise 可以返回一个 promise Compiler.js module.exports = class Compiler { constructor() { this.hooks = { accelerate: new SyncHook(['newspeed']), brake: new SyncHook(), calculateRoutes: new } run(){ this.accelerate(10) this.break() this.calculateRoutes('Async', 'hook', 'demo') } accelerate(speed) { this.hooks.accelerate.call(speed); } break()

2023. Session "Foundational Toolchains" Agenda ● Basic knowledge for interacting with GPUs ● Accelerate Go programs using GPUs ● Challenges in Go when using GPUs ● Conclusion and outlooks 2 Changkun Motivation ○ GPU Driver and Standards ○ Render and compute pipeline ○ Vulkan/Metal/DX12/OpenGL ● Accelerate Go programs using GPUs ● Challenges in Go when using GPUs ● Conclusion and outlooks 3 Changkun 2023. Session "Foundational Toolchains" Agenda ● Basic knowledge for interacting with GPUs ● Accelerate Go programs using GPUs ○ Overall workflow of GPU acceleration ○ Two examples ○ Design Questions

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KER_OPTS --registry-mirror=accelerate address >\"" /lib/systemd/system/docker.service: 1 ExecStart=/usr/bin/dockerd -H fd:// --registry-mirror=accelerate address> /etc/docker/daemon.json: json: 1 { 2 "registry-mirrors": ["accelerate address>"] 3 } Please restart docker service after change the accelerate address: 1 $ sudo service docker restart For the other Linux systems, Windows

--registry-mirror=accelerate address >\"" /lib/systemd/system/docker.service: 1 ExecStart=/usr/bin/dockerd -H fd:// --bip=10.66.0.10/16 --registry-mirror=accelerate address> /etc/docker/daemon /etc/docker/daemon.json: 1 { 2 "registry-mirrors": ["accelerate address>"] 3 } Please restart docker service after change the accelerate address: 1 $ sudo service docker restart 54 欢迎加入 Linux Lab 用户组

--registry-mirror=accelerate address >\"" /lib/systemd/system/docker.service: 1 ExecStart=/usr/bin/dockerd -H fd:// --bip=10.66.0.10/16 --registry-mirror=accelerate address> /etc/docker/daemon /etc/docker/daemon.json: 1 { 2 "registry-mirrors": ["accelerate address>"] 3 } Please restart docker service after change the accelerate address: 1 $ sudo service docker restart 52 欢迎加入 Linux Lab 用户组

memory modules (NVDIMMs). It uses technologies such as soft updates and dual-view directories to accelerate file metadata synchronization and thus improve file read and write performance. • Tiered memory Container Solution Containers are a mainstream cloud computing technology, and simplify encapsulation, accelerate deployments, and reduce environment dependencies. Containers can directly access host resources data, HPC, AI, distributed storage, databases, clouds, and virtualization. This suite can also accelerate applications requiring diversified computing power and for synergy across devices, edge, and