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import pulumi
import pulumi_aws as aws
import pulumi_awsx as awsx
import pulumi_eks as eks
# --- 1. 创建网络 (VPC) ---
# 使用 pulumi_awsx 创建一个 VPC。这个高级组件会自动创建公有和私有子网、
# Internet Gateway、NAT Gateway 等,大大简化了网络配置。
vpc = awsx.ec2.Vpc("my-app-vpc",
number_of_availability_zones=2, # 在两个可用区中创建资源以实现高可用
commit 5db56dd5c2b6c01186e91b6fc0fe993e319c9f46
Author: Li Yazhou <me.ssword@gmail.com>
Date: Wed Jul 9 22:05:01 2025 +0800
poc: use system time for retention & expire
diff --git a/slatedb/src/compaction_execute_bench.rs b/slatedb/src/compaction_execute_bench.rs
index 9b2eba1..4501b98 100644
--- a/slatedb/src/compaction_execute_bench.rs
+++ b/slatedb/src/compaction_execute_bench.rs
use tokio::io::{AsyncReadExt, AsyncWriteExt};
#[tokio::main]
async fn main() {
let mut child = tokio::process::Command::new("cat")
.stdin(std::process::Stdio::piped())
.stdout(std::process::Stdio::piped())
.spawn()
.expect("Failed to spawn cat process");
use object_store::local::LocalFileSystem;
use object_store::aws::{DynamoCommit, S3ConditionalPut};
use object_store::{path::Path, ObjectStore};
use rand::{Rng, RngCore};
use slatedb::config::ReadLevel::Uncommitted;
use slatedb::config::{DbOptions, ObjectStoreCacheOptions, ReadOptions, WriteOptions};
use slatedb::db::Db;
use slatedb::inmemory_cache::InMemoryCacheOptions;
use std::path::PathBuf;
use std::sync::Arc;
ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABgQDKalPVMjfwc6xyDXM9Pp5eync+Jv4VcQ/mSN/RLOPfl+wArIPJjhdJU7GecA6pv/09jt2bqTccgeFLm8ASibmIf5ZWoGMfUXquGuf5nUpadOyeIthfiuiFrWv7PY/MYT13Hh24nWrrvnJ7bDd+Jc7HQ5Y5oiV9fMZKBYLg6rwbLnBpHGGkIIRMhZfvD21/av+IZLnAzE3y0/ZTaY5zY9oQNODkWXEhso1+Jv9GEUj0JpUx4ocjhNTwtOydvFB6SamDE9MQ6l5ICXzlVzRxwT1nfXY3R0kkKGw/qSauzAMuBzB98s/zHXLrs1BEV+MNeGi9mE5MI7FBldjN5+sdbCWNJXc+Mjwl6cLZKMXNg1I8mwk2/2fC75GYDkVYse+zcrsfVc4xRTelAZ9rH6HIWy54SNgnY8BynfRKfF/3yn0oBvUcynov68mT2GRimnlXvhpXb12KM4/eDOPcyz/AZiZ2U4sOi+q/dFU4UjcjwbKWnUZvM6jNyP4RTlDUMIQRU1M= yazhou@yazhous-MBP
text = """
0.01908ms
0.02825ms
0.01729ms
0.03700ms
0.02542ms
0.02700ms
0.04529ms
0.00400ms
0.02742ms
import subprocess
import time
from statistics import mean
# Function to measure the execution time of a command
def measure_time(command):
start_time = time.time()
subprocess.run(command, shell=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
end_time = time.time()
return end_time - start_time
When performing matrix-vector multiplication on the GPU, you can optimize the operation using parallel reduction to efficiently sum up the elements. In a Vulkan compute shader, this could be done using shared memory (local memory in GLSL) to perform a partial sum for each workgroup before completing the sum for the entire vector.
Here's a GLSL compute shader example that demonstrates a reduction pattern for summing elements. The shader assumes that the size of the matrix row (which is the size of the vector) is a power of two for simplicity. This may not be the case in a real-world scenario, so you would need to modify the shader to handle arbitrary sizes.
```glsl
#version 450
// Define the size of the workgroup
layout(local_size_x = 128) in;
goroutine profile: total 60502
30061 @ 0x438cc0 0x448c43 0x835698 0x6c4c74 0x6c6ab5 0x6c8003 0x6c3a7c 0x4688d1
# 0x835697 main.sse+0x787 /data/tmp/portage/net-misc/gossipd-9999/work/src/github.intra.douban.com/push/gossipd/apps/ssed/sse.go:132
# 0x6c4c73 net/http.HandlerFunc.ServeHTTP+0x43 /usr/lib/go/src/net/http/server.go:2012
# 0x6c6ab4 net/http.(*ServeMux).ServeHTTP+0x1a4 /usr/lib/go/src/net/http/server.go:2387
# 0x6c8002 net/http.serverHandler.ServeHTTP+0xa2 /usr/lib/go/src/net/http/server.go:2807
# 0x6c3a7b net/http.(*conn).serve+0x86b /usr/lib/go/src/net/http/server.go:1895
30060 @ 0x438cc0 0x431b9a 0x431105 0x4d41d5 0x4d506b 0x4d504d 0x59c50f 0x5af0ae 0x608950 0x48a7b1 0x608b9c 0x607155 0x60b27b 0x60b286 0x833443 0x4688d1
# 0x431104 internal/poll.runtime_pollWait+0x54 /usr/lib/go/src/runtime/netpoll.go:203
#!/usr/bin/env python
from __future__ import absolute_import, print_function
import os
import sys
import subprocess
import tempfile
import platform
import functools
import codecs