It seems that tinygo doesn't not support MIPS based embedded devices out of the box, although LLVM does support the following:

    mips       - MIPS (32-bit big endian)
    mips64     - MIPS (64-bit big endian)
    mips64el   - MIPS (64-bit little endian)
    mipsel     - MIPS (32-bit little endian)

My intent is to execute the tinygo compiled binary within a mipsel linux box, no

(Noticed whilst reviewing #6695)

From the docs for numba.cuda.atomic.compare_and_swap:

class compare_and_swap(ary, old, val)

Conditionally assign val to the first element of an 1D array ary if the current value matches old.
Returns the current value as if it is loaded atomically.

It seem

Hey everyone!

mapd-core-cpu is already available on conda-forge (https://anaconda.org/conda-forge/omniscidb-cpu)

now we should add some instructions on the documentation.

at this moment it is available for linux and osx.

some additional information about the configuration:

1. for now, always install omniscidb-cpu inside a conda environment (also it is a good practice), eg:

While the test_suite presented in #589 does work, it is still pretty simple and can be improved and enhanced.

• Add tests for gnutils and coreutils.
• Add necessary utilities so more complex programs can be compiled from sources.
• Integrate CMake, so one could write something like make validate and the subset of test that is deemed necessary (for example everything with min t

Scenario:
I have a project, with build tools of cmake, when I try to run it with cling. It prompts some headers are not included.

So I was wondering if there is a way to make use of the cmake script to load the build environment into cling and run directly?

Appreciate the great work!

Currently, the architecture of the CLI is based on (sub)commands and options. Commands are expected to be provided as the first argument, and do effectively decide which feature is to be used. OTOH, options provide parameters to the commands. However, there is no syntactical difference, as both commands and options start with -- or -i. As a result, we rely on properly formating --help and on

enable cyclic-import check in pylint and fix the imports if there are problems

https://blog.llvm.org/posts/2021-01-05-stack-clash-protection/

Appears to be as simple as adding {"probe-stack"="inline-asm"} to all function attributes.

The standard accelerate test suite, used by all the backends, can be quite slow. Several of the tests are significantly slower than the others, for example segmented folds and scans, which I believe is because the reference implementations are very inefficient. Writing some more efficient reference implementations (e.g. using Data.Vector.Unboxed) should help speed things up.