Tuesday, October 31, 2017

[Links of the Day] 31/10/2017 : Machine learning at the edge, Deep Learning on Hardware , operations based CRDT

  • EdgeML : Microsoft research demonstrate how to push machine learning at the edge and run KB models. We could quickly see machine learning enabled IoT device popping around us.  [slides] [github]
  • Efficient Methods and Hardware for Deep Learning : Quest for speed never stop, and often that means getting read of those pesky indirection layers that make your software architecture so flexible :) 
  • Pure Operation-Based Replicated Data Types : CRDT for operations rather than just value. But the core concepts are a little bit tricky and there is some potential pitfall in the approach. Such as the performance limitation and the reliance on causal stability ( which is really hard to obtain in pure decentralised systems)

Thursday, October 26, 2017

[Links of the Day] 26/10/2017 : Algebra for #AI , Live presentation tool, The (nonexistent) CEO effect

  • All the Linear Algebra You Need for AI : well not really, but it is a good start
  • doitlive : if you ever had to do a live demo/presentation. You know how dreadful it can be. Stuff can go wrong really fast. This tool allows you to remove some of the hassles of this type of exercise. It reads a file of shell commands and replays the commands in fake terminal sessions. 
  • How large must the CEO effect be to rule out chance? : turn out that most CEO are completely interchangeable as that most CEO has little effect on company performance. 

Tuesday, October 24, 2017

[Links of the Day] 24/10/2017 : W3C Payment request API, Xen Unicore, Kafka Summit

  • Payment Request API : Interesting to see that now all browser implement the w3c payment api. One step closer to more fluid banking service consumption. 
  • Xen Unicore : Proposal to build a core set of functionality and library allowing users to build unikernels targeted at specific applications without requiring the time-consuming, expert work that building such a unikernel requires today.
  • Kafka Summit : Videos & Slides from the San Francisco 2017 are now available.

Thursday, October 19, 2017

[Links of the Day] 19/10/2017 : Distroless minimal container images, Strangeloop and CppCon 2017

  • Distroless : a toolkit for creating container images which contain only your application and its runtime dependencies. No package shells, managers, any other programs. This is really awesome as you always end up with a lot of clutter in your layer. too often you see apt-get update ; apt-get upgrade in your Dockerfile. Or you could simply move to Golang and enjoy a From scratch environment! [talk] [video]
  • Strangeloop: a very good review of the excellent strange loop conference. Every time I watch some of these talks, I tell myself I should get into functional programming .. Then life ( and three kids under 6 ) takes over. [slides] [videos]
  • CppCon : another dev conference, this time C++. Some interesting talks, especially the includeOS one. Which provides a C++ microkernel functionality by simply including a single header #include ! A lot of in-depth and technical talks, give it a look if you are a C++ dev. [slides] [videos]

Tuesday, October 17, 2017

[Links of the Day] 17/10/2017: Corporate Taxes & wages, Storage with macromolecule, 25 years of MPI

  • Do Higher Corporate Taxes Reduce Wages? : interesting paper where the authors estimate that 40% of the corporate tax burden is passed onto the worker. And that most of the tax variation is directly imposed on the workforce. 
  • Macromolecules as Storage Media : the authors suggest that you can achieve a petabyte per cubic centimetre. Stability and durability are not fully addressed yet compared to another non-organic medium. However, I doubt that this can be a major concern as it can be an extremely viable solution for short-term transport of digital data. 
  • MPI symposium : MPI is 25 years old, and still improving. The venerable HPC message passing interface is still widely used and underpin a lot of non-HPC critical infrastructure such as stock markets. A must read is Jack Dongarra presentation on the evolution of MPI.

Thursday, October 12, 2017

[Links of the Day] 12/10/2017 : bitcoin resource list, time series DB seminar, Microservices debugger

  • Bitcoin resource list : extensive list of bitcoin resource ranging from basic introduction, history, tutorial, to in-depth tech materials
  • Time Series Database Lecture : 2017 Carnegie Mellon university lectures. This is quite good as it not this series of lecture not only offer high-quality theoretical knowledge in the field but also invited talk from key commercial and opensource player in this field ( influxdb, timescale, etc..) 
  • Squash : microservices debugger, because now you can't rely on your monolith debugging skill and tool set anymore ( ^_^).

Tuesday, October 10, 2017

[Links of the Day] 10/10/2017 : Machine Learning Hardware acceleration , Homomorphic encryption

  • Tutorial on Hardware Architectures for Deep Neural Networks : How to leverage hardware for accelerating machine learning processes. 
  • A Survey on Homomorphic Encryption Schemes : this paper presents a thorough survey of the state of homomorphic encryption schemes. Homomorphic encryption allows manipulation of the encrypted data without the need to decrypt it. This will allow when hardware will be fast enough to deal with the complexity of the operations, to have a true secure distributed multitenant database. As no operation on the hosting side will require clear text decryption of the data and everything can be done securely on the client side. 
  • Efficient Methods and Hardware for Deep Learning : Standford lecture where guest lecturer Song Han present algorithms and specialized hardware (FPGA, GPU, ASIC, etc..) that can be used to accelerate training and inference of deep learning workloads. [video]

Friday, October 06, 2017

[Links of the Day] 06/10/2017 : HPC routing topology on dependency graph, Arm network stack development, Multicore graph processing

  • Routing on the Channel Dependency Graph : the author aim are providing a toolset for topology calculation for HPC network. 
  • Arm for network stack developers : arm is trying to slowly move up the stack into the data centre world. For that, it needs to address one of its main limitation: IO. This slide deck describe the current effort to tackle network stack limitation ( and support RDMA ) as well as providing pointer where ARM or devs can push the Linux stack further. As Linux is pretty much the only viable software stack for such hardware infrastructure in the datacenter. 
  • Multicore graph processing : this present a very good overview of the Multicore graph processing problem, solution landscape and where it's heading. Graph problems are essential to solve in the domain of social network modelling as well as for items recommendation or search and website ranking. [slides]

Wednesday, October 04, 2017

[Links of the Day] 04/10/2017 : Tensor Flow Extended , 5d Torus , Machine learning influencing hardware designs

  • TFX : Google paper describing it's tensor flow based platform for production scale deployment. It is impressive how they created a platform that delivers robust TensorFlow-based learners and support for continuous training and serving with production-level reliability. [video]
  • 5d torus : when your 3d torus fabric is not enough :) . The authors demonstrate how using 6 port NIC they are able to achieve such feat. Its domain of application is still be limited to HPC environment as only tailored applications can leverage such network topology. However, there might be potential in the machine learning domain. There is only a future for such approach if they are able to demonstrate significant acceleration for popular problems ( ML ). And make is fungible for cloud-like deployment. I.e. you need to be able to easily partition a set of nodes connected by such network and share it in multitenancy model. [slides] [thesis]
  • Machine Learning and the Implications for Computer System Design : Jeff Dean talk at hot chips 2017 conference. Jeff really really show the current influence of ML on the present and future hardware architecture.