## GCN ## 如何用Go模拟CPU  蒙卓 华为－2012实验室 工程师 ## 成为盘古？ 让这个世界里面的人（程序）无法察觉 这个世界是创造出来的 ## 目录 • 计算机的演化历史 - 硬件计算到冯诺伊曼架构 • 构建虚拟世界 • 6502汇编器与链接器 • 未来目标 1970年程序员 CPU 80KHz 单核 内存 64KB 手编磁芯  老娘把你送上月球 2021年程序员 CPU 2,400,000KHz 4核 内存 8,000,000KB DDR3 为啥现在程序员好像更弱了？ · 因为我们处在最好也是最坏的时代 • 抽象多且环环嵌套 • 硬件过于复杂 • 软件基于操作系统等复杂概念 · 真的快且便宜 ## Go模拟CPU • 如何用Go实现冯诺伊曼架构CPU? • 简单：一个循环+一个大数组 读取当前指令执行指令下一条指令 ## 模拟目标 - MOS 6502 • 诞生于1975年 • MOS 6502应用范围广 · 资料多且易获得

Programs for CPU and GPU ## THOMAS MEJSTRIK ## DIMETOR  FWF ## Bridging the Gap: Writing Portable Programs for CPU and GPU SYCL, ROCm, Vulkan, ... ☐ You can tell me about afterwards ## Why write programs for CPU and GPU ## ☐ Difference CPU/GPU Algorithms are designed differently ☐ Latency/Throughput ☐ Memory bandwidth ☐ radar” - Problem ☐ Why it makes sense? ☐ Scope of the talk ## Why write programs for CPU and GPU ## ☐ Difference CPU/GPU ☐ Why it makes sense? Library/Framework developers ☐ Embarrassingly parallel

## North-South Load Balancing of Kubernetes Services with eBPF/XDP Martynas Pumputis (Isovalent) eBPF Summit  ![Image](

## How and When You Should Measure CPU Overhead of eBPF Programs eBPF Summit ## Why should I profile eBPF programs? ## CI variance tracking ●●●● name TCPLatency/eBPF/kprobe/sys_bind TCPLatency/eB

Startup CPU Usage  2.8 (New) Startup CPU Usage ## Startup Breakdown Enumerate asset files Read localization Load textures textures, models and audio Load game rules & databases  2.7 (Old) Startup Profile  ## High CPU Time Single threaded code Inefficient algorithms Branch misprediction, cache misses Spin locks ## High CPU Time Single threaded code Inefficient algorithms

## CS 591 K1: Data Stream Processing and Analytics Spring 2020 ## 4 /09: Flow control and load shedding Vasiliki (Vasia) Kalavri vkalavri@bu.edu ## Keeping up with the producers • Producers can generate producer (back-pressure, flow control) ## Load management approaches  (a) Load shedding ![Image](/uploads/documents/1/8 transient load increase. ## Scale resource allocation: • Addresses the case of increased load and additionally ensures no resources are left idle when the input load decreases. ## Load shedding • Load shedding

visible，如果不可见，显示 committed。 txnld 为这个 insert 对应的导入事务的 id。 err 字段会显示一些其他非预期错误。 当需要查看被过滤的行时，用户可以通过如下语句 show load where label="xxx"; 返回结果中的 URL 可以用于查询错误的数据，具体见后面 查看错误行 小结。 数据不可见是一个临时状态，这批数据最终是一定可见的 可以通过如下语句查看这批数据的可见状态： from tbl2 where k1 = "a"; ERROR 1064 (HY000): all partitions have no load data. url: http://10.74.167.16:8042/api/_load_error_log?file=__shard_2/error_log_insert_stmt_ba8bb9e158e4879-ae8de8507c0 b9e158e4879_ae8de8507c0bf8a2 其中 ERROR 1064 (HY000): all partitions have no load data 显示失败原因。后面的 url 可以用于查询错误的数据： show load warnings on "url"; 可以查看到具体错误行。 ### 2. 超时时间 INSERT 操作的超时时间由会话变量 query_timeout

tablet writer • Extract & Transform & Load · 汇报导入结果  2. Load 数据 ## Phase 2 ## Publish • 收集导入任务汇报结果 • 发送Publish .jpg) 2. Load 数据 ## Phase 2 ## Publish • 修改BE元数据，数据版本 +1 • 修改FE元数据，数据版本 +1 • 事务状态改为 VISIBLE  2. Load 数据 Phase 2 口Broker Load异步HDFS、BOS对象存储MySQLRoutine Load异步KafkaMySQLStream load同步本地文件，数

HonnetcotricofnhVeMsinhcelusndorgiorhHearbogistrywithaedmpiansswoSd4p dockdorgianuadmi-np**** https://<load_balancer_ip>:443 ## Using Harbor Chartmuseum in Tenant Clusters You acnonf igcalut stpndipdu hk file -> username < usern a m -p a s s w o p r a d s w o < r e p r a m e > https://< LOAD_BALANCER_IP_OF_HARBOR_TENANT> / chartrepo/ < library_n Note • F o c a - f i d e rt - f a n a l l o w i m m g o n d t h e e n c a l n u f t o w n e y r e w a n t u p l o b h d e l c h a r t .load_balancer_ip> ## Step 3 helpusichantame>.tgza-f\d\d\file->-cert-f\b\e\r\file->-key-f\k\l

-> workers) • Bins are selected uniformly at random - At the end of the process, the maximum load is $\Theta(\ln n/\ln \ln n)$, with high probability • Instead, we select d destination bins, each ball at the least full bin: • when d=2, the maximum load is $ \ln \ln n / \ln 2 + O(\tau) $ , with high probability • when d>2, the maximum load keeps decreasing, but only by a constant factor ## Dynamic Dynamic resource allocation • Choose one among n workers • check the load of each worker and send the item to the least loaded one • load checking for every item can be expensive • Choose two workers at