TE
科技回声
首页24小时热榜最新最佳问答展示工作
GitHubTwitter
首页

科技回声

基于 Next.js 构建的科技新闻平台,提供全球科技新闻和讨论内容。

GitHubTwitter

首页

首页最新最佳问答展示工作

资源链接

HackerNews API原版 HackerNewsNext.js

© 2025 科技回声. 版权所有。

Programming on Parallel Machines; GPU, Multicore, Clusters and More

122 点作者 abhi9u超过 1 年前

5 条评论

sweetjuly超过 1 年前
If you feel like you've finally groked GPU/massive parallel software programming and need more challenges, I highly recommend playing around with digital circuits! The level of parallelism available to you in hardware is truly unmatched and it's incredibly fun, especially once you start really pushing implementations of your designs on FPGAs. Granted, FPGAs are frequently less useful than what you could do on a GPU due to the higher clock speeds available on ASICs (if your GPU core clock is 3GHz and your FPGA design maxes out at 500MHz [which would be admirable!], the GPU has nearly 6x the number of cycles to match or beat your implementation!).
评论 #38341928 未加载
JZL003超过 1 年前
I know it depends on the analysis, but I often am doing somewhat embarassingly parallel things. So just knowing GNU parallel for mid-scale things (and R/python basically parallelism, although shared memory is a bear), and how to temporarily scale across the cloud to like 500 core, is huge.
评论 #38341474 未加载
评论 #38341485 未加载
infocollector超过 1 年前
For anyone who knows both R and Python well - Request: I think it would be nice to translate this book into Python from R.
评论 #38340009 未加载
spiritplumber超过 1 年前
I like the Parallax Propeller for this if you need a microcontroller. $8 for 8 cores.
jsyang00超过 1 年前
Is MPI still widely used?
评论 #38341778 未加载
评论 #38340912 未加载