"hardware" entries

Four short links: 26 March 2015

Four short links: 26 March 2015

GPU Graph Algorithms, Data Sharing, Build Like Google, and Distributed Systems Theory

  1. gunrocka CUDA library for graph primitives that refactors, integrates, and generalizes best-of-class GPU implementations of breadth-first search, connected components, and betweenness centrality into a unified code base useful for future development of high-performance GPU graph primitives. (via Ben Lorica)
  2. How to Share Data with a Statisticiansome instruction on the best way to share data to avoid the most common pitfalls and sources of delay in the transition from data collection to data analysis.
  3. Bazela build tool, i.e. a tool that will run compilers and tests to assemble your software, similar to Make, Ant, Gradle, Buck, Pants, and Maven. Google’s build tool, to be precise.
  4. You Can’t Have Exactly-Once Delivery — not about the worst post office ever. FLP and the Two Generals Problem are not design complexities, they are impossibility results.
Comment
Four short links: 24 March 2015

Four short links: 24 March 2015

Tricorder Prototype, Web Performance, 3D Licensing, and Network Simulation

  1. Tricorder Prototypecollar+earpiece, base station, diagnostic stick (lab tests for diabetes, pneumonia, tb, etc), and scanning wand (examine lesions, otoscope for ears, even spirometer). (via Slashdot)
  2. Souders Joins SpeedcurveDuring these engagements, I’ve seen that many of these companies don’t have the necessary tools to help them identify how performance is impacting (hurting) the user experience on their websites. There is even less information about ways to improve performance. The standard performance metric is page load time, but there’s often no correlation between page load time and the user’s experience. We need to shift from network-based metrics to user experience metrics that focus on rendering and when content becomes available. That’s exactly what Mark is doing at SpeedCurve, and why I’m excited to join him.
  3. 3 Steps for Licensing Your 3D-Printed Stuff (PDF) — this paper is not actually about choosing the right license for your 3D printable stuff (sorry about that). Instead, this paper aims to flesh out a copyright analysis for both physical objects and for the digital files that represent them, allowing you to really understand what parts of your 3D object you are—and are not—licensing. Understanding what you are licensing is key to choosing the right license. Simply put, this is because you cannot license what you do not legally control in the first place. There is no point in considering licenses that ultimately do not have the power to address whatever behavior you’re aiming to control. However, once you understand what it is you want to license, choosing the license itself is fairly straightforward. (via BoingBoing)
  4. Augmented Traffic Control — Facebook’s tool for simulating degraded network conditions.
Comment
Four short links: 19 March 2015

Four short links: 19 March 2015

Changing Behaviour, Building Filters, Public Access, and Working Capital

  1. Using Monitoring Dashboards to Change Behaviour[After years of neglect] One day we wrote some brittle Ruby scripts that polled various services. They collated the metrics into a simple database and we automated some email reports and built a dashboard showing key service metrics. We pinpointed issues that we wanted to show people. Things like the login times, how long it would take to search for certain keywords in the app, and how many users were actually using the service, along with costs and other interesting facts. We sent out the link to the dashboard at 9am on Monday morning, before the weekly management call. Within 2 weeks most problems were addressed. It is very difficult to combat data, especially when it is laid out in an easy to understand way.
  2. Quiet Mitsubishi Cars — noise-cancelling on phone calls by using machine learning to build the filters.
  3. NSF Requiring Public AccessNSF will require that articles in peer-reviewed scholarly journals and papers in juried conference proceedings or transactions be deposited in a public access compliant repository and be available for download, reading, and analysis within one year of publication.
  4. Filtered for Capital (Matt Webb) — It’s important to get a credit line [for hardware startups] because growing organically isn’t possible — even if half your sell-in price is margin, you can only afford to grow your batch size at 50% per cycle… and whether it’s credit or re-investing the margin, all that growth incurs risk, because the items aren’t pre-sold. There are double binds all over the place here.
Comment
Four short links: 12 March 2015

Four short links: 12 March 2015

Billion Node Graphs, Asynchronous Systems, Deep Learning Hardware, and Vision Resources

  1. Mining Billion Node Graphs: Patterns and Scalable Algorithms (PDF) — slides from a CMU academic’s talk at C-BIG 2012.
  2. There Is No NowOne of the most important results in the theory of distributed systems is an impossibility result, showing one of the limits of the ability to build systems that work in a world where things can fail. This is generally referred to as the FLP result, named for its authors, Fischer, Lynch, and Paterson. Their work, which won the 2001 Dijkstra Prize for the most influential paper in distributed computing, showed conclusively that some computational problems that are achievable in a “synchronous” model in which hosts have identical or shared clocks are impossible under a weaker, asynchronous system model.
  3. Deep Learning Hardware GuideOne of the worst things you can do when building a deep learning system is to waste money on hardware that is unnecessary. Here I will guide you step by step through the hardware you will need for a cheap high performance system.
  4. Awesome Computer Vision — curated list of computer vision resources.
Comment
Four short links: 11 March 2015

Four short links: 11 March 2015

Working Manager, Open Source Server Chassis, Data Context, and Coevolved Design & Users

  1. As a Working Manager (Ian Bicking) — I look forward to every new entry in Ian’s diary, and this one didn’t disappoint. But I’m a working manager. Is now the right time to investigate that odd log message I’m seeing, or to think about who I should talk to about product opportunities? There’s no metric to compare the priority of two tasks that are so far apart. If I am going to find time to do development I am a bit worried I have two options: (1) Keep doing programming after hours; (2) Start dropping some balls as a manager.
  2. Introducing Yosemite (Facebook) — a modular chassis that contains high-powered system-on-a-chip (SoC) processor cards.
  3. The Joyless World of Data-Driven StartupsThere is so much invisible, fluid context wrapped around a data point that we are usually unable to fully comprehend exactly what that data represents or means. We often think we know, but we rarely do. But we really WANT it to mean something, because using data in our work is scientific. It’s not our decision that was wrong — we used the data that was available. Data is the ultimate scapegoat.
  4. History of the Urban Dashboardthe dashboard and its user had to evolve in response to one another. The increasing complexity of the flight dashboard necessitated advanced training for pilots — particularly through new flight simulators — and new research on cockpit design.
Comment
Four short links: 10 March 2015

Four short links: 10 March 2015

Robot Swarms, Media Hacking, Inside-Out Databases, and Quantified Medical Self

  1. Surgical Micro-Robot SwarmsA swarm of medical microrobots. Start with cm sized robots. These already exist in the form of pillbots and I reference the work of Paolo Dario’s lab in this direction. Then get 10 times smaller to mm sized robots. Here we’re at the limit of making robots with conventional mechatronics. The almost successful I-SWARM project prototyped remarkable robots measuring 4 x 4 x 3mm. But now shrink by another 3 orders of magnitude to microbots, measured in micrometers. This is how small robots would have to be in order to swim through and access (most of) the vascular system. Here we are far beyond conventional materials and electronics, but amazingly work is going on to control bacteria. In the example I give from the lab of Sylvain Martel, swarms of magnetotactic bacteria are steered by an external magnetic field and, interestingly, tracked in an MRI scanner.
  2. Media Hacking — interesting discussion of the techniques used to spread disinformation through social media, often using bots to surface/promote a message.
  3. Turning the Database Inside Out with Apache Samzareplication, secondary indexing, caching, and materialized views as a way of getting into distributed stream processing.
  4. Apple Research Kit — Apple positioning their mobile personal biodata tools with medical legitimacy, presumably as a way to distance themselves from the stereotypical quantified selfer. I’m reminded of the gym chain owner who told me, about the Nike+, “yeah, maybe 5% of my clients will want this. The rest go to the gym so they can eat and drink what they want.”
Comment
Four short links: 24 February 2015

Four short links: 24 February 2015

Open Data, Packet Dumping, GPU Deep Learning, and Genetic Approval

  1. Wiki New Zealand — open data site, and check out the chart builder behind the scenes for importing the data. It’s magic.
  2. stenographer (Google) — open source packet dumper for capturing data during intrusions.
  3. Which GPU for Deep Learning?a lot of numbers. Overall, I think memory size is overrated. You can nicely gain some speedups if you have very large memory, but these speedups are rather small. I would say that GPU clusters are nice to have, but that they cause more overhead than the accelerate progress; a single 12GB GPU will last you for 3-6 years; a 6GB GPU is plenty for now; a 4GB GPU is good but might be limiting on some problems; and a 3GB GPU will be fine for most research that looks into new architectures.
  4. 23andMe Wins FDA Approval for First Genetic Test — as they re-enter the market after FDA power play around approval (yes, I know: one company’s power play is another company’s flouting of safeguards designed to protect a vulnerable public).
Comment
Four short links: 23 February 2015

Four short links: 23 February 2015

Self-Assembling Chairs, Home Monitoring, Unicorn Horn, and Cloud Security

  1. MIT Scientists and the Self-Assembling Chair (Wired) — using turbulence to randomise interactions, and pieces that connect when the random motions align. From the Self-Assembly Lab at MIT.
  2. Calaosa free software project (GPLv3) that lets you control and monitor your home.
  3. Founder Wants to be a Horse Not a Unicorn (Business Insider) — this way of thinking  —  all or nothing moonshots to maximise shareholder value  —  has become pervasive dogma in tech. It’s become the only respectable path. Either you’re running a lowly lifestyle business, making ends meet so you can surf all afternoon, or you’re working 17-hour days goring competitors with your $US48MM Series C unicorn horn on your way to billionaire mountain.
  4. Using Google Cloud Platform for Security Scanning (Google Online Security) — platform vendors competing on the things they can offer for free on the base platform, things which devs and ops used to have to do themselves.
Comment
Four short links: 20 February 2015

Four short links: 20 February 2015

Robotic Garden, Kids Toys, MSFT ML, and Twitter Scale

  1. The Distributed Robotic Garden (MIT) — We consider plants, pots, and robots to be systems with different levels of mobility, sensing, actuation, and autonomy. (via Robohub)
  2. CogniToys Leverages Watson’s Brain to Befriend, Teach Your Kids (IEEE) — Through the dino, Watson’s algorithms can get to know each child that it interacts with, tailoring those interactions to the child’s age and interests.
  3. How Machine Learning Ate Microsoft (Infoworld) — Azure ML didn’t merely take the machine learning algorithms MSR had already handed over to product teams and stick them into a drag-and-drop visual designer. Microsoft has made the functionality available to developers who know the R statistical programming language and Python, which together are widely used in academic machine learning. Microsoft plans to integrate Azure ML closely with Revolution Analytics, the R startup it recently acquired.
  4. Handling Five Billion Sessions a Day in Real Time (Twitter) — infrastructure porn.
Comments: 2
Four short links: 18 February 2015

Four short links: 18 February 2015

Sales Automation, Clone Boxes, Stats Style, and Extra Orifices

  1. Systematising Sales with Software and Processes — sweet use of Slack as UI for sales tools.
  2. Duplicate SSH Keys EverywhereIt looks like all devices with the fingerprint are Dropbear SSH instances that have been deployed by Telefonica de Espana. It appears that some of their networking equipment comes set up with SSH by default, and the manufacturer decided to reuse the same operating system image across all devices.
  3. Style.ONS — UK govt style guide covers the elements of writing about statistics. It aims to make statistical content more open and understandable, based on editorial research and best practice. (via Hadley Beeman)
  4. Warren Ellis on the Apple WatchI, personally, want to put a gold chain on my phone, pop it into a waistcoat pocket, and refer to it as my “digital fob watch” whenever I check the time on it. Just to make the point in as snotty and high-handed a way as possible: This is the decadent end of the current innovation cycle, the part where people stop having new ideas and start adding filigree and extra orifices to the stuff we’ve got and call it the future.
Comment