siboehm.com valuation and analysis
Robots.txt Information
| Robot | Path | Permission |
| GoogleBot | / | ✔ |
| BingBot | / | ✔ |
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Meta Tags
| Title | siboehm |
| Description | Simon Boehm’s technical |
| Keywords | N/A |
Server Information
| WebSite | |
| Host IP | 185.199.110.153 |
| Location | - |
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siboehm.com Valuation
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US$1,094,015
Last updated: 2023-05-15 00:13:40
siboehm.com has Semrush global rank of 9,674,737. siboehm.com has an estimated worth of US$ 1,094,015, based on its estimated Ads revenue. siboehm.com receives approximately 126,233 unique visitors each day. Its web server is located in -, with IP address 185.199.110.153. According to SiteAdvisor, siboehm.com is safe to visit. |
Traffic & Worth Estimates
| Purchase/Sale Value | US$1,094,015 |
| Daily Ads Revenue | US$1,010 |
| Monthly Ads Revenue | US$30,296 |
| Yearly Ads Revenue | US$363,550 |
| Daily Unique Visitors | 8,416 |
| Note: All traffic and earnings values are estimates. | |
DNS Records
| Host | Type | TTL | Data |
| siboehm.com. | A | 1798 | IP: 185.199.110.153 |
| siboehm.com. | A | 1798 | IP: 185.199.111.153 |
| siboehm.com. | A | 1798 | IP: 185.199.109.153 |
| siboehm.com. | A | 1798 | IP: 185.199.108.153 |
| siboehm.com. | NS | 1800 | NS Record: dns2.registrar-servers.com. |
| siboehm.com. | NS | 1800 | NS Record: dns1.registrar-servers.com. |
| siboehm.com. | MX | 1799 | MX Record: 10 mxext2.mailbox.org. |
| siboehm.com. | MX | 1799 | MX Record: 20 mxext3.mailbox.org. |
| siboehm.com. | MX | 1799 | MX Record: 10 mxext1.mailbox.org. |
| siboehm.com. | TXT | 1799 | TXT Record: v=spf1 include:mailbox.org |
| siboehm.com. | TXT | 1799 | TXT Record: google-site-verification=AVEqmpV54mPKS8GQ1OW-P2AQf8EVrL3Df4nIjmbgYB0 |
HtmlToTextCheckTime:2023-05-15 00:13:40
| siboehm About siboehm This is the website of Simon Boehm. I work on making code run faster at the Astera Institute . If you like these posts: Subscribe to the mailing list. How to Optimize a CUDA Matmul Kernel for cuBLAS-like Performance: a Worklog In this post, I’ll iteratively optimize an implementation of matrix multiplication written in CUDA. My goal is not to build a cuBLAS replacement, but to deeply understand the most important performance characteristics of the GPUs that are used for modern deep learning. This includes coalescing global memory accesses, shared memory caching and occupancy optimizations, among others. You can download the code for all kernels from Github . Also checkout wangzyon’s repo from which I copied the benchmarking setup. This post is less polished than my normal uploads, and includes many more sidenotes. I used it as notepad for ideas and scribbles while writing the kernels. That’s why I called it a worklog :) Pipeline-Parallelism: Distributed Training |
HTTP Headers
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siboehm.com Whois Information
Domain Name: SIBOEHM.COM Registry Domain ID: 2417261626_DOMAIN_COM-VRSN Registrar WHOIS Server: whois.namecheap.com Registrar URL: http://www.namecheap.com Updated Date: 2021-06-27T07:38:19Z Creation Date: 2019-07-27T13:15:30Z Registry Expiry Date: 2022-07-27T13:15:30Z Registrar: NameCheap, Inc. Registrar IANA ID: 1068 Registrar Abuse Contact Email: abuse@namecheap.com Registrar Abuse Contact Phone: +1.6613102107 Domain Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited Name Server: DNS1.REGISTRAR-SERVERS.COM Name Server: DNS2.REGISTRAR-SERVERS.COM DNSSEC: unsigned >>> Last update of whois database: 2021-12-20T07:26:07Z <<< |