intel-scipy

SciPy optimized with Intel(R) MKL library

Project description

Optimized implementation of scipy, leveraging Intel® Math Kernel Library to achieve highly efficient multi-threading, vectorization, and memory management. Accelerates scipy's linear algebra and Fourier transform capabilities. Drop-in replacement that maintains API compatibility with scipy. Additional details can be found in our SciPy 2017 conference proceedings.

One of many Intel® accelerated Python packages and performance library runtimes available on PyPI, and as part of Intel® Distribution for Python.

For latest release updates and security notifications, please subscribe to the Intel® Distribution for Python Community forum.

Free to use and redistribute pursuant to the Intel Simplified Software License.

Project details

Release history Release notifications | RSS feed

This version

1.1.0

Sep 25, 2018

1.0.1

Jun 14, 2018

1.0.0.0

Nov 16, 2017

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for intel-scipy, version 1.1.0
Filename, size	File type	Python version	Upload date	Hashes
Filename, size intel_scipy-1.1.0-cp27-cp27m-macosx_10_12_intel.macosx_10_12_x86_64.whl (28.5 MB)	File type Wheel	Python version cp27	Upload date Sep 25, 2018	Hashes View
Filename, size intel_scipy-1.1.0-cp27-cp27mu-manylinux1_x86_64.whl (22.9 MB)	File type Wheel	Python version cp27	Upload date Sep 25, 2018	Hashes View
Filename, size intel_scipy-1.1.0-cp27-cp27m-win_amd64.whl (20.7 MB)	File type Wheel	Python version cp27	Upload date Sep 25, 2018	Hashes View
Filename, size intel_scipy-1.1.0-cp35-cp35m-manylinux1_x86_64.whl (22.7 MB)	File type Wheel	Python version cp35	Upload date Sep 27, 2018	Hashes View
Filename, size intel_scipy-1.1.0-cp36-cp36m-macosx_10_12_intel.macosx_10_12_x86_64.whl (28.2 MB)	File type Wheel	Python version cp36	Upload date Sep 25, 2018	Hashes View
Filename, size intel_scipy-1.1.0-cp36-cp36m-manylinux1_x86_64.whl (22.7 MB)	File type Wheel	Python version cp36	Upload date Sep 25, 2018	Hashes View
Filename, size intel_scipy-1.1.0-cp36-cp36m-win_amd64.whl (23.8 MB)	File type Wheel	Python version cp36	Upload date Sep 25, 2018	Hashes View

Hashes for intel_scipy-1.1.0-cp27-cp27m-macosx_10_12_intel.macosx_10_12_x86_64.whl

Hashes for intel_scipy-1.1.0-cp27-cp27m-macosx_10_12_intel.macosx_10_12_x86_64.whl
Algorithm	Hash digest
SHA256	`d703eba14991992109439e4924219d541bb59e1fe17a81182701b11114605e31`
MD5	`cc1f40a637736485c8490bc2126332bd`
BLAKE2-256	`7005127dceb04288c23920f0f0a5feac026b155764a17a5d003a0de847af325e`

Hashes for intel_scipy-1.1.0-cp27-cp27mu-manylinux1_x86_64.whl

Hashes for intel_scipy-1.1.0-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`24d6c01ad4d2f1bfc70e1e945addfa2627f46c7cee64c8613ae1a5363e32a117`
MD5	`c972a614be35da7b284dd9f793776c48`
BLAKE2-256	`298c0a14ade9cc0e93f21df1534bf1d2c59f7cd96b2c4c9b595ccb6085fda628`

Hashes for intel_scipy-1.1.0-cp27-cp27m-win_amd64.whl

Hashes for intel_scipy-1.1.0-cp27-cp27m-win_amd64.whl
Algorithm	Hash digest
SHA256	`97bf06cc1663f173e8115407e47f8cddbc4e06da0ff210a9d9d8f8cafdbb629e`
MD5	`3642b6e4842a62854833cf337af6d2db`
BLAKE2-256	`cbd849c4d38c8baf3ec0dd6767ccb48dadd04ff878a8043d93c2d87ecb310aa0`

Hashes for intel_scipy-1.1.0-cp35-cp35m-manylinux1_x86_64.whl

Hashes for intel_scipy-1.1.0-cp35-cp35m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`5e9c49f323286325600de48e55cefc4ba1372e60f52b8113a678d81445f37132`
MD5	`0e0b653d73b6e0cb6033c9117dce4a6a`
BLAKE2-256	`999c36046531835d761d4488638c0c234b79a9bde5aff75a5f18b0d53d997a54`

Hashes for intel_scipy-1.1.0-cp36-cp36m-macosx_10_12_intel.macosx_10_12_x86_64.whl

Hashes for intel_scipy-1.1.0-cp36-cp36m-macosx_10_12_intel.macosx_10_12_x86_64.whl
Algorithm	Hash digest
SHA256	`c36040effba3b542f785db111b7ace77a233f79d94b05d058aeb5f555f745631`
MD5	`1acad786cf9bfff9c6100e15e64a1972`
BLAKE2-256	`15091cbb81d6eeae4fb10aa14a7cc0ec38cd555c12a392481b5c126517ed2014`

Hashes for intel_scipy-1.1.0-cp36-cp36m-manylinux1_x86_64.whl

Hashes for intel_scipy-1.1.0-cp36-cp36m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`bc59d79e916594f562fe9db1cfecc17e5c7c9df2293626daa2f22adce1b791c9`
MD5	`8b843d517ded21046a3c55465121270f`
BLAKE2-256	`ab6fb5dd831c5655d06504c0740f415a52246c7223163208141c617dae7a1b3b`

Hashes for intel_scipy-1.1.0-cp36-cp36m-win_amd64.whl

Hashes for intel_scipy-1.1.0-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`f58adffe86a64804b3aa0face0d5aeb00ea8dbe62a50874a0f618b8d6218b1c6`
MD5	`0f07240ba3c8a8acfbef51af425ce310`
BLAKE2-256	`b359faebc69a598a22e4a021694b3d4cd431b46ea026c1f0c229e071e2ff12b1`