Show HN: Enhanced GNU Awk https://ift.tt/8clEUHW

Show HN: Enhanced GNU Awk https://ift.tt/gteZ0xf April 13, 2022 at 07:03AM

Show HN: A Simple Memory Game https://ift.tt/Vw74toU

Show HN: A Simple Memory Game https://ift.tt/iV98Jd2 April 13, 2022 at 05:08AM

Show HN: Razer x Lambda Tensorbook https://ift.tt/qi5967n

Show HN: Razer x Lambda Tensorbook Hi all, long time lurker, first time poster. I want to share with you all something we've been working on for a while at Lambda: the Razer x Lambda Tensorbook: https://www.youtube.com/watch?v=wMh6Dhq7P_Q But before I tell you about it, I want to make this all about me, because I built this for me. See, while I'm genuinely interested in hearing from the community what you think as this is the culmination of a lot of effort from a lot of people across so many different fields (seriously, the number of folks across manufacturing, engineering, design, logistics, and marketing who have had to work together to launch this is nuts), I really just want to tie the larger motivations for Tensorbook as a product back to a personal narrative to explain why I'm so proud. So, flashback to 2018, and I'm a hardware engineer focusing on the compute system at Lyft's autonomous vehicle (AV) program, Level5 (L5). Here was a project that that would save lives, that would improve the human condition, that was all ready to go. I saw my role as coming in to product-ize, to take what was close to the finish line and get it over it. The disappointment was pretty brutal when I realized just how wrong I was. It's one thing to nod along when reading Knuth write "premature optimization is the root of all evil"; it's another to experience it firsthand. At Lyft L5 I thought I would be applying specialized inference accelerators (Habana, Groq, Graphcore, etc.) into the vehicle compute system. Instead, the only requirement that mattered org-wide was: "Don't do anything that slows down the perception team". Forget testing silicon with the potential to reduce power requirements by 10x, I was lucky to get a willing ear to hear my case for changing a flag in the TensorFlow runtime to perform inference at FP16 instead of FP32. Don't get me wrong, there were a multitude of other difficult technical challenges to solve outside of the deep learning ones that were gating, but I had underestimated just how not-ready the CNNs for object detection and classification were. Something I thought was a solved problem was very much not, and ultimately resulted in my team and others building a 5,000 watt monster of server (+ power distribution, + thermals, + chassis, etc etc) that took up an entire rear row of seating. I'm happy to talk about that experience in the comments because I have a lot of fond memories from my time there. Anyway, the takeaway I have from Lyft, and my first motivation here is that there is no such thing as over-provisioning or too much compute in a deep learning engineer's mind. Anything less than the most possible is a detriment to their workflow. I still truly believe AVs will save lives; so by extension, enabling deep learning engineers enables AVs enables improvement to the human condition. Transitive property, :thumbsup: So moving on, my following role in industry was characterized by working closely with the least technical people I have ever had the opportunity to work with in my life. And I mean opportunity genuinely, because doing so gave me so much perspective on the things that you and I here probably take for granted. (How do we know that Ctrl+Alt+T will open a terminal? Why does `touch` make a file? How do I quit vim?) So, the takeaway from that experience, and motivation #2 for me is that computers can be so unaccessible in surprising ways. I have a deep respect and appreciation for Linux, and I want others to see things the same way, so anything I can do to make easier the process of "self-serving" or "bootstrapping" to my level of understanding, is something worth doing to me. So, with those two personal motivations outlined, I present to you, for your consideration, the Razer x Lambda Tensorbook. A laptop with a no-compromise approach to speeds-and-feeds and shipping with OEM support for Ubuntu. sincerely, Vinay. Product Marketing @ Lambda April 13, 2022 at 12:12AM

Show HN: Oregon State University Class Data Explorer https://ift.tt/MtdeJ2G

Show HN: Oregon State University Class Data Explorer https://ift.tt/48fcx9Y April 12, 2022 at 04:51AM

Show HN: ToolJet v1.10 The open-source alternative to Retool https://ift.tt/Neyg50h

Show HN: ToolJet v1.10 The open-source alternative to Retool https://ift.tt/B062URt April 12, 2022 at 07:02AM

Show HN: Esht – Embeddable SHell Tags https://ift.tt/rXwvzG6

Show HN: Esht – Embeddable SHell Tags https://ift.tt/tmTSsIn April 12, 2022 at 02:15AM

Show HN: Multiplayer Demo Built with Elixir https://ift.tt/FuOAPVw

Show HN: Multiplayer Demo Built with Elixir Hey HN, I’m an engineer at Supabase [0] and one of the creators of this demo. My team and I have been working hard to bring developers the next version of Supabase Realtime. The current version of Realtime [1] is a Change Data Capture (CDC) server for a PostgreSQL database that broadcasts changes via WebSockets to authorized subscribers. It’s written in Elixir/Phoenix. The server utilizes PostgreSQL’s logical replication functionality, which writes database changes to Write-Ahead Logging (WAL) segment files, and a replication slot, responsible for managing and retaining WAL files. Database changes are polled from WAL by the server using PostgreSQL’s replication function pg_logical_slot_get_changes and changes converted to JSON objects using the wal2json [2] extension by setting it as the output plugin. Security is enforced through two checks - each check ensures only authorized client subscribers are sent database changes. The first check validates a JWT that is sent by clients subscribing to database changes. This JWT must contain an existing database role and optional claims, both of which can be referenced in Row Level Security (RLS) policies. Every valid client subscription is then inserted into the realtime.subscription table with an assigned UUID, database role, and claims. The second check calls the realtime.apply_rls SQL function from Write Ahead Log Realtime Unified Security (WALRUS) utility lib [3]. This function takes the database changes, executes a prepared statement to verify if the database role and claims have SELECT permissions on the changes, and outputs an array of authorized UUIDs. Then, the server finds all the subscribers whose UUIDs are in that array and broadcasts the changes to them. The next version of Supabase Realtime will offer three features: Broadcast, Presence, and Extensions. Broadcast, our Pub/Sub offering, can be used to pass ephemeral data from client to client such as cursor movements. This runs on a distributed cluster of nodes built on top of Phoenix PubSub + Channels. Presence, can be used for tracking online/offline users and their state. This is built into Phoenix, and uses replicated state across a cluster using an Observe-Remove-Set-Without-Tombstones (ORSWOT) CRDT [4] which prefers adds over removes when resolving conflicts. Extensions, are a way for the community to add additional functionality to take advantage of the WebSocket infrastructure. We have converted the existing Change Data Capture system to an extension that supports connecting to multiple customer databases (multi-tenancy). Other possible extensions include listening to other databases like MySQL and getting stock market events server-side [5], then broadcasting them to connected clients. This demo is built using a Supabase project, Supabase Realtime, and Next.js and deployed on 20 Fly [6] nodes located around the world. You can find an introduction and walkthrough of the demo here [5]. Supabase Realtime is entirely open source and you can find the demo code here [7]. Once we have stabilized the release we will add it to the self-hosted offering [8]. This demo is a way to highlight the upcoming features and gather feedback/ideas. Feel free to ask me anything and let me know what you think! [0] https://supabase.com [1] https://ift.tt/AZF5HfN [2] https://ift.tt/nXetGsa [3] https://ift.tt/uSMWDyF [4] https://ift.tt/608qPmw... [5] https://ift.tt/4stGIyb... [6] https://fly.io [7] https://ift.tt/kgjpYSb [8] https://ift.tt/XhfViQN https://multiplayer.dev April 11, 2022 at 11:45PM