saxpy | Python implementation of Symbolic Aggregate approXimation | Math library

by nphoff Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | saxpy Summary

saxpy is a Python library typically used in Utilities, Math applications. saxpy has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However saxpy build file is not available. You can download it from GitHub.

An implementation of Symbolic Aggregate approXimation in python. Based on the paper A Symbolic Representation of Time Series, with Implications for Streaming Algorithms. You can optionally specify word size, alphabet size and epsilon.

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Support

saxpy has a low active ecosystem.

It has 90 star(s) with 47 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 4 have been closed. On average issues are closed in 134 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of saxpy is current.

Quality

saxpy has 0 bugs and 0 code smells.

Security

saxpy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

saxpy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

saxpy is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

saxpy releases are not available. You will need to build from source code and install.

saxpy has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

saxpy saves you 66 person hours of effort in developing the same functionality from scratch.

It has 172 lines of code, 21 functions and 2 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed saxpy and discovered the below as its top functions. This is intended to give you an instant insight into saxpy implemented functionality, and help decide if they suit your requirements.

Generate a sliding window based sliding window
Convert a numpy array to a PCA matrix
Returns the alphabetized X
Normalize data
Convert a sequence of words to a regular expression
Compare a list of strings
Compute the distance between two strings
Compare two letters

Get all kandi verified functions for this library.

saxpy Key Features

No Key Features are available at this moment for saxpy.

saxpy Examples and Code Snippets

No Code Snippets are available at this moment for saxpy.

Community Discussions

Trending Discussions on saxpy

Why PyCUDA is faster than C CUDA in this example

Calling Fortran OpenACC from CUDA file. How to compile with PGI?

Can I change the formula of SAXPY function?

Why am I getting a syntax error in a previously tested code at "__kernel void smth(.."?

C++ implicitly transform trivially constructable struct to member

C++ Convert tuple of homogeneous wrapped type to tuple of raw type

How does cudaLaunchKernel know the array size of "void **args"?

BLAS function returns zero in Fortran90

Segfault when using clCreateCommandQueueWithProperties

Why repeating a kernel inside a for-loop makes CUDA code significantly slower?

QUESTION

Why PyCUDA is faster than C CUDA in this example

Asked 2021-Mar-02 at 06:42

I am exploring to move from OpenCL to CUDA, and did a few tests to benchmark the speed of CUDA in various implementations. To my surprise, in the examples below, the PyCUDA implementation is about 20% faster than the C CUDA example.

I read many posts talking about "release build" of C CUDA code. I did try having -Xptxas -O3 in the makefile and that really did not make a difference. I also tried to adjust the block size, with which the kernel was executed. Unfortunately, it did not help improve the speed, either.

My questions here are:

What could be the reasons leading to the speed difference between C CUDA and PYCUDA?
If the "advanced" (lack of a better word) compiling in PYCUDA is one of reasons, how can I optimize the compiling of my C CUDA code?
Are there any other ways to improve the speed of C CUDA in this case?

While I appreciate general comments, I am looking for actionable suggestions that I can validate on my machine. Thanks!

...

ANSWER

Answered 2021-Mar-01 at 21:36

If I execute your CUDA-C code as is, and set num_iterations to 300 like this:

Source https://stackoverflow.com/questions/66427688

QUESTION

Calling Fortran OpenACC from CUDA file. How to compile with PGI?

Asked 2020-Mar-30 at 14:30

I have a CUDA code in which I would like to include external code that consists of Fortran with OpenACC kernels. I have two files with the following content inspired on a discussion on the NVIDIA website. File main.cu is the following:

...

ANSWER

Answered 2020-Mar-30 at 14:30

The symbols are most likely missing since you're not adding either the OpenACC or Fortran runtime libraries to your link. Also, when not using a PGI driver to link, you need to add the "nordc" flag. For example:

Source https://stackoverflow.com/questions/60929456

QUESTION

Can I change the formula of SAXPY function?

Asked 2019-Dec-02 at 20:28

I am new to GPGPU, and I have a confusion about SAXPY function: The SAXPY function is like given two same sizes and type vector X and Y, do the operation that changes each element in Y: y[i] = y[i]+a*x[i]

I am not sure of can we change SAXPY's formula, like: y[i]=(y[i]+a)*(x[i]+c)

but in this case, there is a new constant c, I have no idea how to call SAXPY in this condition.

Thanks for your valuable time.

...

ANSWER

Answered 2019-Dec-02 at 20:28

I have no idea how to call SAXPY in this condition.

You cannot.

Saxpy is abbreviation for (nvidia docs):

Single-Precision A·X Plus Y

A possible implementation is:

Source https://stackoverflow.com/questions/59145272

QUESTION

Why am I getting a syntax error in a previously tested code at "__kernel void smth(.."?

Asked 2019-Jun-20 at 02:18

I used this code from another example in StackOverflow instead of my own code. Both give out the same syntax mistake at void

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ANSWER

Answered 2019-Jun-20 at 02:18

That code looks like OpenCL -- it isn't Python code, and won't run in a Python shell.

Source https://stackoverflow.com/questions/56673868

QUESTION

C++ implicitly transform trivially constructable struct to member

Asked 2019-Jan-25 at 00:27

I feel that its unlikelier than not, but I'd like to see if a function can deduce its parameters from a trivially wrapped struct. For example:

...

ANSWER

Answered 2019-Jan-25 at 00:27

From the comments, I was not aware that C++ had a casting operator. The simple solution is to add:

Source https://stackoverflow.com/questions/54357120

QUESTION

C++ Convert tuple of homogeneous wrapped type to tuple of raw type

Asked 2019-Jan-23 at 16:45

I'd like to call std::apply() to a function; however, I am unable to because the std::tuple I use is currently wrapped. For example:

...

ANSWER

Answered 2019-Jan-23 at 09:44

I would avoid std::apply completely and call the callback directly by unpacking the tuple using std::index_sequence:

Source https://stackoverflow.com/questions/54323759

QUESTION

How does cudaLaunchKernel know the array size of "void **args"?

Asked 2018-Dec-25 at 14:51

I know the size of array can be got with following code:

...

ANSWER

Answered 2018-Dec-25 at 14:51

Quoting from the related documentation:

The number of kernel parameters and their offsets and sizes do not need to be specified as that information is retrieved directly from the kernel's image.

Every CUDA device function has its argument list stored with the statically compiled function code. The API, therefore, knows exactly how many argument entries a call to cudaLaunchKernel requires. You will get a segfault or undefined behaviour if you supply too few to the launch call.

Source https://stackoverflow.com/questions/53920500

QUESTION

BLAS function returns zero in Fortran90

Asked 2018-May-14 at 15:13

I am learning to use BLAS in Fortran90, and wrote a simple program using the subroutine SAXPY and the function SNRM2. The program computes the distance between two points by subtracting one vector from the other, then taking the euclidean norm of the result.

I am specifying the return value of SNRM2 as external according to the answer to a similar question, "Calling BLAS functions". My full program:

...

ANSWER

Answered 2018-May-14 at 15:13

According to this page, there seems to be some issue with single precision routines in the BLAS shipped with Apple's Accelerate Framework. On my Mac (OSX10.11), gfortran-8.1 (installed via Homebrew) + default BLAS (in the system) gives a wrong result:

Source https://stackoverflow.com/questions/50316681

QUESTION

Segfault when using clCreateCommandQueueWithProperties

Asked 2018-Feb-09 at 00:27

I'm trying to write an OpenCL wrapper in C++. Yesterday I was working on my Windows 10 machine (NVIDIA GTX970 Ti, latest NVIDIA GeForce drivers I believe) and my code worked flawless.

Today, I'm trying it out on my laptop (Arch Linux, AMD Radeon R7 M265, Mesa 17.3.3) and I get a segfault when trying to create a command queue.

Here's the GDB backtrace:

...

ANSWER

Answered 2018-Feb-09 at 00:27

clCreateCommandQueueWithProperties got added in OpenCL 2.0. You should not use it with platforms and devices that are less than version 2.0 (such as 1.1 and 1.2 shown in your logs).

Source https://stackoverflow.com/questions/48686503

QUESTION

Why repeating a kernel inside a for-loop makes CUDA code significantly slower?

Asked 2018-Jan-06 at 00:34

Suppose we have four float arrays to be used on the host side, as well as its four counterparts to be used on the device side:

...

ANSWER

Answered 2017-Feb-28 at 22:29

A simple change solves the problem, but I would still very much appreciate learning the technical reasons for all this.

The solution is to merely change, in my toy example above, the kernel to:

Source https://stackoverflow.com/questions/42519157

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install saxpy

You can download it from GitHub.
You can use saxpy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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