1. Jindo Directly Accelerating OSS Set the environment variables 1 2 3 4 5 6 7 export ENDPOINT=oss-cn-beijing-internal.aliyuncs.com export BUCKET= export AK= export SK= export NAMESPACE=default export PVC=myoss-jindo export URI=datacenter Create the credentials 1 2 3 4 5 6 7 8 9 10 11 kubectl apply -f - <<EOF apiVersion:

1. About JuiceFS Caching On a host, warmed cache is placed directly on the host. In a cluster, there are two levels of cache: Worker, which provides cache shared at the cluster level Fuse, which provides cache at the current node level only 2. Warming Data with the JuiceFS Client Note that warming at the Fuse layer is only effective for the current node; if you need to warm the whole cluster, you must warm at the Worker layer.

1. Install the Driver Create the HwHiAiUser user 1 2 groupadd -g 1000 HwHiAiUser useradd -g HwHiAiUser -u 1000 -d /home/HwHiAiUser -m HwHiAiUser -s /bin/bash Add directory permissions 1 2 chown -R HwHiAiUser /usr/local/Ascend chmod -R 755 /usr/local/Ascend Download the driver and firmware Go to https://www.hiascend.ru/hardware/firmware-drivers/community?product=1&model=30&cann=All&driver=1.0.26.alpha to find the matching driver and firmware.

1. Storage Tiering and Interconnect 2. Various Storage Types Storage Type Bandwidth Capacity Response Latency Cost per Unit of Storage Storage Principle Use Case CPU L1 Cache 256-512GB/s 32-64KB/core <1ns ~$2000/MB SRAM Closest cache layer to CPU core CPU L2 Cache 64-256GB/s 256KB-2MB/core group 2-5ns ~$1000/MB Partly SRAM, partly embedded DRAM Next-level cache for the CPU CPU L3 Cache 32-128GB/s 4-16MB/CPU 5-15ns ~$100-200/MB Embedded DRAM Last-level cache for the CPU GPU L1 Cache 8-32TB/s 16-96KB/SM <1ns ~$2000/MB SRAM Closest cache layer to GPU core GPU L2 Cache 1-4TB/s 512KB-4MB/SMC 5-15ns ~$500-1000/MB Partly SRAM, partly embedded DRAM Next-level cache for the GPU Main memory (RAM) 10-80GB/s 4-128GB 30-60ns ~$2-7/GB DDR4/5 DRAM System main storage space GPU VRAM 768GB/s-4TB/s 4-24GB 25-75ns ~$7-20/GB GDDR6/6X SDRAM Dedicated high-speed buffer storage for the GPU SSD 500MB/s-7000MB/s 128GB-8TB 0.

1. Create the Dataset 1 2 3 4 5 6 7 8 9 10 kubectl apply -f - <<EOF apiVersion: v1 kind: Secret metadata: name: my-s3 type: Opaque stringData: aws.accessKeyId: xxx aws.secretKey: xxx EOF 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 kubectl apply -f - <<EOF apiVersion: data.