I've read somewhere that the current machine model is not quite fit for functional programming. So what is the limitations of the current machine model? Has a more suitable machine model been developed?
Landin's SECD machine was one of the first designed to evaluate lambda calculus expressions. Ager et al. cover other abstract and virtual machines designed to do same in their paper "A Functional Correspondence between Evaluators and Abstract Machines".
Yes, it was developed. Here's an article on Lisp Machine.
Related
I need the old version of Google Translate (the statistical model, the version before 2016) for my research,
I was wondering if there any way to access the old version?
Thanks
See the update below
Original answer
Yes, as of 2020, Google Translate statistical machine translation still available as phrase-based machine translation.
https://cloud.google.com/translate/docs/basic/translating-text
Using the model parameter
You can specify which model to use for translation by using the model query parameter. Specify base to use the PBMT model, and nmt to use the NMT model. If you specify the NMT model in your request and the requested language translation pair is not supported for the NMT model, then the PBMT model is used.
There are similar options for the Microsoft API and the undocumented Google APIs.
My guess is that there are no statistical systems available for newly added language pairs - a major advantage of massive multilingual models is not having to train or deploy separate systems for the long tail.
Update
No, Google ended statistical machine translation in August 2021.
https://cloud.google.com/translate/docs/release-notes#August_02_2021
August 02, 2021
changed
Removed the Phrase-Based Machine Translation (PBMT) model. For requests that specify the PBMT model, Cloud Translation uses the Neural Machine Translation (NMT) model instead.
https://cloud.google.com/translate/docs/basic/translating-text#model
Note: Translation previously offered a Phrase-Based Machine Translation (PBMT) model (also known as the base model). If you specify that model for translations, Translation uses the NMT model instead.
I doubt it is running somewhere. The statistical system is a complicated pipeline that is expensive to run and difficult to maintain.
You can try contacting someone from Google Research who works on MT (just have a look at papers on arXiv, the authors have contact emails there) if they can run it for you.
Alternatively, you can build your own Moses system, it is an open-source implementation of statistical MT, so the results should be similar to what was Google Translate (judging from the WMT competitions results before 2016).
You can try to check Google Translate in the Web Archive.
I use R, but lately are trying to implement Model Predictive Control as applied in Control Engineering on my models, but it seems that this area in R is non-existent as compared to Matlab where it is quite easy to do System Identification and create transfer functions which can be deployed inside the Model Predictive Control module. Anybody knows where to look, or which packages to use for MPC and transfer functions in R to build MPC models?
There are a growing number of Python packages for control engineering. One option is to use the reticulate R package to interface to Python functions. Here are some Control Engineering packages in Python:
SciPy.signal for signal processing and system modeling
SymPy for Laplace transforms and differential equation analytic solutions
Control Systems Library
Chemical Process Control from Jeff Kantor, Notre Dame
Process Dynamics and Control in Python at BYU (my course)
Advanced Control and Machine Learning in Python at BYU (also my course)
Here is an example of running MPC in Python on the Temperature Control Lab.
I am learning SOA for our new project. I want to know basic information on SOA modelling technologies. I saw lot many terminologies in internet like SoaML, BPMN, SOMF, SOMA, SOBA ... and confused when/where to use what modelling technology.
Please help me to identify exact technology to model our services.
Thanks in Advance.
SOAML - UML Profile (Modeling notation) for modeling SOA.
BPMN - Modeling notation for for modeling business processes.
SOMF - Methodology for designing SOA architectures. From Michael Bell. Supported by tools like Sparx Enterprise Architect
SOMA - Methodology for designing SOA architectures. From IBM. Supported by RSA.
Haven't heard of SOBA.
Model your services using the simplest tool you can, I use blocks and line drawings for the overview (service) level models and UML sequence diagrams for depicting internal orchestration.
The modelling language will not help you learn how to build SOA, experience of doing and following best practices will help.
Good luck and enjoy the journey
Has everyone migrated to MPI (message passing interface) or is PVM still widely used in supercomputers and HPC?
My experience is that PVM is not widely utilized in high-performance computing. MPI seems widely used and something like co-array Fortran might be the path forward for massively parallel systems of the future.
I use a library called InterComm to couple physics models together as separate executables. InterComm currently utilizes PVM for communication between these coupled models. PVM and InterComm boast that they work on homogeneous and heterogeneous network environments (I've been told MPI does not support heterogeneous compute/network environments). However, this is a feature that we've never used (and I highly doubt we ever will).
I have had a difficult time running PVM on academic compute environments. Some sys-admin/support-type people at reputable national computing centers have even suggested that we "simply" re-code our 20 year-old O(10^4) line code to use MPI because of issues we ran into while porting the code to a particular supercomputer in which the router/queing environment didn't like launching multiple parallel executables alongside PVM.
If you're at the architecture/design stage of a project, I'd recommend staying away from PVM unless you need to work on heterogeneous compute/network environments!
It may be highly site-dependent but in my experience MPI completely
dominates PVM in the (academic at least) HPC space. You can't
realistically launch a new HPC interconnect without MPI support but
PVM seems to be decidedly optional. Is there a PVM implementation for
Infiniband for instance?
I am looking for symbolic mathematics library for .NET framework. I have looked at Math.net but it's not something usable yet. Do you know if there is another library exists?
This might be overkill, but you can talk to Mathematica from .NET, using its .NET/Link API.
Symbolism is a library which implements automatic simplification of algebraic expressions in C#. It can be used as a foundation for more complex symbolic mathematics operations.