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Synthesizable register(s) can conventionally be verified using access technique that use address & data buses (these buses are very much part of the actual hardware present on the silicon chip). But this conventional access technique consumes finite time.
Register Abstraction Layer (RAL) with UVM is a very efficient way of verifying RTL registers in your design. One of the key features of this methodology is 'backdoor access', by virtue of which one can access (i.e. read from or write into) any RTL register(s) in zero simulation time. The backdoor access mechanism uses hierarchical HDL paths to do so.
The question is what physical provisions on the silicon makes this, access-in-zero-time, possible?
You don't use any special physical provisions on silicon to enable backdoor access. UVM is used with simulation and in simulation you can have access to the values of any signal in the design. At most, a designer could create some throw away signal for you to collect bits of a register that are scattered throughout the design.
The Register Abstraction Layer in the UVM provides backdoor access to registers using techniques only available during simulation. This could be through hierarchical references not allowed by synthesis tools, or using a tool programming interface like the the DPI. So backdoor here refers to a simulation tool's ability to modify the state of the design.
There is, of course, backdoors in design that circumvent the normal hardware protocol for accessing registers, but that is a functional aspect of the design and would never occur in 0 time. A scan chain would be an example of backdoor hardware access.
None, obviously. Zero access time is physically impossible. You should verify your design before committing it to silicon.
I am trying to determine which of these two to buy for my work. I have used SIMULINK but not LabVIEW. Is there anyone who has used both and would like to provide some details? My investigation criteria are the user friendliness, availability of libraries and template functions, real-time probing facility, COTS hardware interfacing opportunity, quality of code generation, design for testability (i.e. ease of generating unit/acceptance tests), etc. However, if anyone would like to educate me with more criteria, please do so by all means!
For anyone who does not know about SIMULINK and LabVIEW - These are both Domain-Specific Languages (DSLs) intended for graphical dataflow modelling (and also code generation). These are multi-industrial tools and quite heavily used for engineering design and modelling.
IMPORTANT - I am quite interested to know if SIMULINK and LabVIEW offer real-time probing. For example, I have a model that I want to simulate. If there are variables associated to certain building blocks in that model, could I view them changing as the simulation continues? I know that it is certainly not possible with SIMULINK as it has a step-by-step debugger. I am not aware of anything similar in LabVIEW.
I really have not used LabVIEW and cannot obtain it temporarily as my work internet has got download restrictions and administrative privilege issues. This is the reason why I simply cannot use only NI website to draw conclusions. If there is any white paper available that addresses this issue, I would also love to know :)
UPDATE SINCE LAST POST
I have used MATLAB code generator and will not say that it is the best. However, I hear now that SIMULINK Embedded Coder is the best code generator and almost one of its own kind. Can anyone confirm whether or not this is good for safety critical system design i.e. generating code from safety-critical subsystem models. I know that the Mathworks is constantly trying to close the gap to achieve fully-flexible production-level C/C++ code generation.
I know that an ideal answer would be,"Depending on what you are trying to do, use a bit of both". And interestingly, I think I am heading to that direction. ATEOTD, it is a lot of money and need to be spent "nicely".
Thanks in advance.
I used labVIEW from 1995, and Simulink from 2000. Now I am involved in control system design, and simulation of robotic systems using labVIEW Real Time and automotive ECUs using MATALAB/Simulink/DSPACE .
LabVIEW is focus on measurement systems, and MATLAB/SIMULINK in dynamic simulation, so,
If you run complex simulations, and your work is create/debug complex simulation models of controllers or plants, use Simulink+RealTimeWorkShop+StateFlowChart. LabVIEW has no eficient code generators for dynamic simulation. RTW generates smaller and fastest code.
If your main work is developing systems with controllers and GUI for machines, or you want to deploy the controllers on field, use labVIEW.
If your main work is developing flexible HIL or SIL systems, with a good GUI, you can use VeriStand. Veristand can mix Simulink and LabVIEW code.
And if you have a big budget ( VERY BIG ) and you are working in automotive control prototypes, DSPACE hardware is a very good choice for fast development of automotive ECUS, or OPAL to develope electric power circuits. But only for prototype or HIL testing of controllers.
From the point of view of COTS hardware:
Mathworks don´t manufacture hardware -> Matlab/Simulink support hardware from several vendors.
National Instruments produce/sell hardware->LabVIEW Real Time is focused in support NationalInstruments hardware. There are no COTS full replacement.
I have absolutely no experience with Simulink, so I'll comment only on LV, although a quick read about Simulink on Wikipedia seems to indicate that it's focused mainly on simulation and modelling, which is certainly not the case with LabVIEW.
OK, so first of all, LV is NOT a DSL. While you wouldn't want to use it for any project, it's a general purpose programming language and you should take that into account. I know that NI has a simulation toolkit for LV, which might help you if that's what you're after, but I have absolutely no experience with it. The images I saw of it seemed to indicate that it adds a special kind of diagram to LV for simulation.
Second, LV is not restricted to any kind of hardware. It's a general purpose language, so you can write code which won't use any hardware at all, code which will use or run on NI's hardware or code which will use any hardware (be it through DLL calls, .NET assemblies, RS232, TCP, GPIB or any other option you can think of). There is quite a large collection of LV drivers for various devices and the quality of the driver usually depends on who wrote it.
Third, you can certainly probe in real time in LV. You write your code, just as you would in C or Java, and when you run it, you have several debugging options:
Single stepping. This isn't actually all that common, partially because LV is parallel.
Execution highlighting. This runs the code in slow motion, while showing all the values in the various wires.
Probes, which show you the last value that each wire had, where wires fill the same function that variables do in text based languages. This updates in real time and I assume is what you want.
Retain wire values, which allows you to probe a wire even after data passed through it. This is similar to what you get in text based IDEs with variables. In LV you don't usually have it because wire values are transient, so the value is not kept around unless you explicitly ask for it.
Of course, since you're talking about code, you could also simply write the code to display the values to the screen on a graph or a numeric indicator or to log them to a file, so there should be no need for actual probing. You could also add analysis code, etc.
Fourth, you could try downloading and running LV in a fully functional evaluation mode. If I remember correctly, NI currently gives you 7 days and then 45 days if you register on their site. If you can't do that on a work computer, you could try at home. If your problem is only with downloading, you could try contacting your local NI office and asking them to send you a DVD.
Note that I don't really know anything about modelling and simulation, so I have no idea what kind of code you would actually have to write in order to do what you want. I assume that if NI has a special module for it, then it's not something that you can completely cover in regular code (at least not if you want the original notation), but I would say that if you could write the code that does what you want in C, there's no reason you shouldn't be able to write it in LV (assuming, of course, that you know how to write code in LV).
A lot of the best answer would have to depend on your ultimate design requirements. Are you developing a product? If so, in what stage of development are you? Or are you doing research?
I recently did a comparison just as you are doing. I know LV, but was wanting to move towards a more hardware-scalable option, since NI HW is very expensive in volume. That is, my company was wanting to move towards a product. What LV and NI HW give you is flexibility. You can change code very quickly compared to C. On the other hand, LV does not run on nearly as many different HW platforms as C. So I wanted to find an inexpensive platform that would work well for real-time control and data acquisition, such that if we wanted to sell a product for, say, $30k, our controller wouldn't be costing $15k of that. We ended up with Diamond Systems Linux SBC's. Interestingly, Simulink ended up using the most expensive hardware! It did have a lot of flexibility, and could generate code, as well as model plants and controllers. But then, LV can do that as well.
As Yair wrote, LV has plenty of good debugging tools. One of the more interesting tools that is not so well known is the Suspend when Called option for a SubVI. This allows you to play with the inputs and outputs of a SubVI as much as you want while execution is paused.
MATLAB and Simulink are the defacto standard for control system design and simulation. Simulink controller models can be used for offline simulation in conjunction with plant models, all the way to realtime implementation on embedded targets. It is a general simulation framework with extensive built-in libraries as well as a la carte special purpose libraries, and can be extended through creation of custom blocks (S-function blocks) in C and other languages. It includes the ability to display values in graphs, numeric displays, gages, etc. while a nonrealtime simulation is taking place. Realtime target support from The Mathworks includes x86 (xPC Target) and several embedded targets (MPC555, etc.), and there is 3rd party support for other targets. The aforementioned dSPACE provides complete prototyping controllers including support for their quite powerful hardware. xPC Target includes support for a plethora of COTS PC data acquisition cards. Realtime target support includes GUI elements such as graphs, numeric displays gages, etc.
As I understand it (I have never really used it in anger), LabView only supports NI hardware, and is more hardware-oriented. Simulink supports hardware from multiple vendors, be it for data acquisition, or real-time implementation, but it may require a bit more work for the user to interface to his or her own hardware (less plug & play than LabView). On the other hand, Simulink provides tools to support the whole model-based design process, from modelling & simulation, control design, verification & validation, code generation, hardware-in-the-loop, etc...
Disclaimer: I used to work for MathWorks.
You guys may really be interested in Control Design adn Simulation Module for LabVIEW. It does a lot of simulations and in the future may be competitive to Simulink. I'm not a control engineer but I use it sometimes for simple testing and I'm glad that I don't have to learn Simulink from the beginning to do some work since I'm familiar with LabVIEW philosophy.
I am starting an AR project for a client which involves using AR in order to show information about certain objects. In this project, for example, the user would point the camera at a car. Depending on which part of the car the user is looking at (headlights, windshield) a button would appear. When the user presses that button, an information window would appear on screen, giving the user more information about that certain car part.
The client doesn't wish to place physical markers on the car (QR code / patterns), and so the car parts would have to be detected another way.
I have developed AR apps before, but based on user location and generated markers in the sky. I feel this system wouldn't be entirely relevant for the client's request.
Would anybody be able to point me in the right direction (iOS library) for this sort of project, and whether or not it would be entirely feasible.
Thanks for the input,
Andy.
What you need is a model-based tracker/6DOF object tracker. As you want to track a car, it will certainly be featureless (or you will only get sparse features), so you should look at textureless non planar 3D (object) tracking solutions.
It's pretty much state of the art right now (lot of research, few products/SDK), but using library like OpenCV and with the appropriate literature (see below) you should be able to develop one. You can look at an open-source solution like the ViSP library which has a module for model based tracker but not an official iOS port. for commercial libraries, closest will be AR libraries supporting SLAM or "3D object tracking".
In term of techniques, you have different way to handle this problem, some pointers:
You can use a model-based tracker relying on edge detection + initial CAD model of the object: 3D Textureless Object Detection and Tracking: An Edge-based Approach or Harald Wuest, Folker Wientapper, Didier Stricker Adaptable Model-based Tracking Using Analysis-by-Synthesis Techniques
The 12th International Computer Analysis of Images and Patterns (CAIP), 27-29th August 2007, Vienna, Austria.
You can use a model-based tracker relying on edge detection + (trained) template images
You can use some SLAM techniques combined with a model based tracker.
M. Tamaazousti, V. Gay-Bellile, S. Naudet Collette, S. Bourgeois, M. Dhome Real-Time Accurate Localization in a Partially Known Environment:Application to Augmented Reality on textureless 3D Objects. TrakMark 2011, Basel, Switzerland 26-29/10/2011
if your system will only run indoor, you can look at some RGBD tracker
S. Hinterstoisser, V. Lepetit, S. Ilic, S. Holzer, G. Bradski, K. Konolige, N. Navab
Model Based Training, Detection and Pose Estimation of Texture-Less 3D Objects in Heavily Cluttered Scenes Asian Conference on Computer Vision (ACCV), Korea, Daejeon, November 2012
(access to the software)
It seems you are heading for an interesting topic. However, my concern is the accuracy of what you are trying to do. Location-based AR would be a starting point for your research work. Still the granularity would be less to your problem domain. Since you have worked on the location-based AR application, you might have noticed the accuracy that you can expect would be maximum upto 3 meters. Therefore, that level of accuracy cannot address your problem domain in an advanced way.
However, I have seen prototypes that addresses your problem domain. One good example would be the BMW Augmented Reality Manual. Check this link http://www.youtube.com/watch?v=P9KPJlA5yds
Hence, I never came across a proper Augmented Reality library for iOS or even Android which can address your problem domain in the marker-less AR context.
The information above is only for your knowledge, but not to discourage you in any way.
Currently I am trying to create an app for iPhone which is capable of recognizing the objects on an image such as car, bus, building, bridge, human, etc, and label as object name with the help of Internet.
Is there any free service which provide solution to my problem, as object recognition its self a complex algorithm requiring digital image processing, neural networks and all.
Can this can be done via API?
If you want to recognise planar images the current generation of mobile AR SDKs from Metaio, Qualcomm and Layar will allow you to upload images to match against, and perform the matching.
If you want to match freely against a set of 3D objects, e.g. a Toyota Prius or the Empire state, the same techniques might be applied to match against sets of images taken at different rotations, but you might have to choose to match just one object due to limitations on how large an image database you can have with the service, or contact those companies for a custom solution, and it may not work very reliably given the state of the art is to reliably match against planar images.
If you want to recognize general classes (human, car, building), this is a very difficult problem, and I don't know of any solutions anywhere fast enough to operate online (which I assume is a requirement given you want an AR solution - is that a fair assumption?). It's been a few years since I studied CV, but at that time the most promising solution for visual classification was "bag of visual words" approaches - you might try reading up on those.
Take a look at Cortexica. Very useful for this sort of thing.
http://www.cortexica.com/
I haven't done work with mobile AR in a while, but the last time I was working on this stuff I was using Layar and starting to investigate Junaio. Those are oriented toward 3D graphics, not simply text labels, so for your use case you may be better served with OpenCV.
Note that Layar (and I believe Junaio too) works like a web app, where you put the content on your own server and give Layar the URL to link to.
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To learn FPGA programming, I plan to code up a simple Neural Network in FPGA (since it's massively parallel; it's one of the few things where an FPGA implementation might have a chance of being faster than a CPU implementation).
Though I'm familiar with C programming (10+ years). I'm not so sure with FPGA development stuff. Can you provide a guided list of what I should do / learn / buy?
Thanks!
Necroposting, but for others like me that come across this question there is an in-depth, though old, treatment of implementing neural networks using FPGAs
It's been three years since I posted this, but it is still being viewed so I thought I'd add another two papers from last year I recently found.
The first talks about FPGA Acceleration of Convolutional Neural Networks. Nallatech performed the work. It's more marketing that an academic paper, but still an interesting read, and might be a jumping off point for someone interesting in experimenting. I am not connected to Nallatech in any way.
The second paper came out of the University of Birmingham, UK, written by Yufeng Hao. It presents A General Neural Network Hardware Architecture on FPGA.
Most attempts at building a 'literal' neural network on an FPGA hit the routing limits very quickly, you might get a few hundred cells before P&R pulls takes longer to finish than your problem is worth waiting for. Most of the research into NN & FPGA takes this approach, concentrating on a minimal 'node' implementation and suggesting scaling is now trivial.
The way to make a reasonably sized neural network actually work is to use the FPGA to build a dedicated neural-network number crunching machine. Get your initial node values in a memory chip, have a second memory chip for your next timestamp results, and a third area to store your connectivity weights. Pump the node values and connection data through using techniques to keep the memory buses saturated (order node loads by CAS line, read-ahead using pipelines). It will take a large number of passes over the previous dataset as you pair off weights with previous values, run them through DSP MAC units to evaluate the new node weights, then push out to the result memory area once all connections evaluated. Once you have a whole timestep finished, reverse the direction of flow so the next timestep writes back to the original storage area.
I want to point out a potential issue with implementing a Neural Network in FPGA. FPGAs have limited amount of routing resources. Unlike logic resources (flops, look-up tables, memories), routing resources are difficult to quantify. Maybe a simple Neural Network will work, but a "massively parallel" one with mesh interconnects might not.
I'd suggest starting with a simple core from OpenCores.org just to get familiar with FPGA flow, and then move on to prototyping a Neural Network. Downloading free Xilinx WebPack, which includes ISIM simulator, is a good start. Later on you can purchase a cheap dev. board with a small FPGA (e.g. Xilinx Spartan 3) to run your designs on.
A neural network may not be the best starting point for learning how to program an FPGA. I would initially try something simpler like a counter driving LEDs or a numeric display and build up from there. Sites that may be of use include:
http://www.fpga4fun.com/ - Excellent examples of simple projects and some boards.
http://opencores.org/ - Very useful reference code for many interfaces, etc...
You may also like to consider using a soft processor in the FPGA to help your transition from C to VHDL or Verilog. That would allow you to move small code modules from one to the other to see the differences in hardware. The choice of language is somewhat arbitrary - I code in VHDL (syntactically similar to ADA) most of the time, but some of my colleagues prefer Verilog (syntactically similar to C). We debate it once in a while but really it's personal choice.
As for the buyers / learners guide, you need:
Patience :) - The design cycle for FPGAs is significantly longer than for software due to the number of extra 'free parameters' in the build, so don't be surprised if it takes a while to get designs working exactly the way you want.
A development board - For learning, I would buy one from one of the three bigger FPGA vendors: Xilinx, Altera or Lattice. My preference is Xilinx at the moment but all three are good. For learning, don't buy one based on the higher-end parts - you don't need to when starting using FPGAs. For Xilinx, get one based on the Spartan series such as the SP601 (I have one myself). For Altera, buy a Cyclone one. The development boards will be significantly cheaper than those for the higher-end parts.
A programming cable - Most companies produce a USB programming cable with a special connector to program the devices on the board (often using JTAG). Some boards have the programming interface built in (such as the SP601 from Xilinx) so you don't need to spend extra money on it.
Build tools - There are many varieties of these but most of the big FPGA vendors provide a solution of their own. Bear in mind that the tools are only free for the smaller lower-performance FPGAs, for example the Xilinx ISE Webpack.
The software comprises stages with which you may not be familiar having come from the software world. The specifics of the tool flow are always changing, but any tool you use should be able to get from your code to your specific device. The last part of this design flow is normally provided by the FPGA vendor because it's hardware-specific and proprietary.
To give you a brief example, the software you need should take your VHDL and Verilog code and (this is the Xilinx version):
'Synthesise' it into constructs that match the building blocks available inside your particular FPGA.
'Translate & map' the design into the part.
'Place & route' the logic in the specific device so it meets your timing requirements (e.g. the clock speed you want the design to run at).
Regardless of what Charles Stewart says, Verilog is a fine place to start. It reminds me of C, just as VHDL reminds me of ADA. No one uses Occam in industry and it isn't common in universities.
For a Verilog book, I recommend these especially Verilog HDL. Verilog does parallel work trivially, unlike C.
To buy, get a relatively cheap Cyclone III eval board from [Altera] or Altera's 3 (e.g. this Cyclone III one with NIOS for $449 or this for $199) or Xilinx.
I'll give you yet a third recommendation: Use VHDL. Yes, on the surface it looks like ADA. While Verilog bears a passing resemblance to C. However, with Verilog you only get the types that come with it out of the box. With VHDL you can define your own new types which lets you program at a higher level (still RTL, of course). I'm pretty sure the Xilinx and Altera free tools support both VHDL and Verilog. "A Designers Guide to VHDL" by Ashenden is a good VHDL book.
VHDL has a standard fixed-point math package which can make NN implementation easier.
It's old, because I haven't thought much about FPGAs in nearly 20 years, and it uses a concurrent programming language that is rather obscure, but Page & Luk, 1991, Compiling Occam into FPGAs covers some crucial topics in a nice way, enough, I think, for your purposes. Two links for trying stuff out:
KRoC is an actively maintained, linux-based Occam compiler, which I know has an active user base.
Roger Peel has a logic synthesis page that has some documentation of his linux-based workflow from Occam code synthesis through to FPGA I/O.
Occam->FPGA isn't where the action is, but it may be a much better place to start than, say, Verilog.
I would recommend looking into xilinx high-level synthesis, especially if you are coming from a C background. It abstracts away the technical details in using a hdl so the designer can focus on the algorithmic implementation.
The are restriction in the type of C code you can write. For example, you can't use dynamically sized data structures, as that would infer dynamically sized hardware.