Release Notes

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.23.0] - 2024-05-28

Fixed

  • Array alignment problem for stack arrays allocated for kernel arguments. (#1357)

  • Issue #892, #906 caused by incorrect code generation for indexing (#1377)

  • Generation of KernelHasReturnValueError error inside KernelDispatcher. (#1394)

  • Issue #1390: broken support for slicing into dpctl.tensor.usm_ndarray in kernels (#1425)

  • Support for Wheels package on Windows (#1430)

  • Incorrect mangled name for kernel function arguments (#1443)

  • Remove artifacts from conda/wheel packages residing in root level (#1450)

  • GDB tests to work properly on Intel Max GPU (#1451)

  • Improper wheels installation on unsupported platforms (#1452)

  • Ref-counting of Python object temporaries in unboxing code (#1454)

  • Segfault caused by using malloc to allocate NRT_MemInfo. Replaced with Numba’s NRT alloc (#1458)

  • Incorrect package name in README.md (#1463)

Added

  • A new overloaded dimensions attribute for all index-space id classes (#1359)

  • Support for AtomicRef creation using multi-dimensional arrays (#1367)

  • Support for linearized indexing functions inside a JIT compiled kernel (#1368)

  • Improved documentation: overview (#1341), kernel programming guide (#1388), API docs (#1414), configs options (#1415), comparison with SYCL API (#1417)

  • New PrivateArray class in kernel_api to replace dpex.private.array (#1370, #1377)

  • Support for libsycinterface::DPCTLKernelArgType enum for specifying type of kernel args instead of hard coding (#1382)

  • New indexing unit tests for kernel_api simulator and JIT compiled modes (#1378)

  • New unit tests to verify all kernel_api features usable inside device_func (#1391)

  • A sycl::local_accessor-like API (kernel_api.LocalAccessor) for numba-dpex kernel (#1331)

  • Specialization support for device_func decorator (#1398)

  • Support for all kernel_api functions inside the numba_dpex.kernel decorator. (#1400)

  • Support for dpnp 0.15 (#1434, #1464)

  • Improvements to pyproject.toml configs to build numba-dpex from source. (#1449)

  • Load the SPV_INTEL_variable_length_array SPIR-V extension to supporting arrays in private address-space on Intel Max GPU. (#1451)

Changed

  • Default inline threshold value set to 2 from None. (#1385)

  • Port parfor kernel templates to kernel_api (#1416), (#1424)

  • Use SPIRVKernelDispatcher for parfor kernel dispatch (#1435, #1448)

  • All examples use the latest dpctl API (#1431)

  • Minimum required dpctl version is now 0.16.1

  • Minimum required numba version is now 0.59.0 (#1462)

Removed

  • OpenCL-like kernel API functions (#1420)

  • func decorator (replaced by device_func) (#1400)

  • numba_dpex.experimental.kernel and numba_dpex.experimental.device_func (#1400)

[0.22.0] - 2024-02-19

Fixed

  • Bug in boxing a DpnpNdArray from parent (#1155)

  • Strided layouts and F-contiguous layouts supported in experimental kernel (#1178)

  • Barrier call code-generation on OpenCL CPU devices (#1280, #1310)

  • Importing numba-dpex can break numba execution (#1267)

  • Overhead on launching numba_dpex.kernel functions (#1236)

Added

  • Support for dpctl.SyclEvent data type inside dpjit (#1134)

  • Support for kernel_api.Range and kernel_api.NdRange inside dpjit (#1148)

  • DPEX_OPT: a numba-dpex-specific optimization level config option (#1158)

  • Uploading wheels packages to anaconda (#1160)

  • flake8 eradicate linter option (#1177)

  • Support dpctl.SyclEvent.wait call inside dpjit (#1179)

  • Creation of sycl event and queue inside dpjit (#1193, #1190, #1218)

  • Experimental kernel dispatcher for kernel compilation (#1178, #1205)

  • Added experimental target context for SPIRV codegen (#1213, #1225)

  • GDB test cases in public CI (#1209)

  • Async kernel submission option (#1219, #1249)

  • A new literal type to store IntEnum as Literal types (#1227)

  • SYCL-like memory enum classes to the experimental module (#1239)

  • call_kernel function to launch kernels (#1260)

  • Experimental overloads for an AtomicRef class and fetch_* methods (#1257, #1261)

  • New device-specific USMNdArrayModel for USMNdArray and DpnpNdArray types (#1293)

  • Experimental atomic load, store and exchange operations (#1297)

  • Kernel_api module to simulate kernel functions in pure Python (#1304, #1326)

  • Experimental implementation of group barrier operation (#1280)

  • Experimental atomic compare_exchange implementation (#1312)

  • Experimental group index class (#1310)

  • OpenSSF scorecard (#1320)

  • Experimental feature index overload methods (#1323)

  • Experimental feature group index overload methods (#1330)

  • API Documentation for kernel API (#1332)

Changed

  • Switch to dpc++ compiler for building numba-dpex (#1210)

  • Versioneer and pytest configs into pyproject.toml (#1212)

  • numba-dpex can be imported even if no SYCL device is detected by dpctl (#1272)

Removed

  • Kernel launch params as lists/tuple. Only Range/NdRange supported (#1251)

  • DEFAULT_LOCAL_SIZE global constant (#1291)

  • Functions to invoke spirv-tools utilities from spirv_generator (#1292)

  • Incomplete vectorize decorator from numba-dpex (#1298)

  • Support for Numba 0.57 (#1307)

Deprecated

  • OpenCL-like kernel API functions in numba_dpex.ocldecl module

[0.21.4] - 2023-10-12

Fixed

  • Remove dead code to silence Coverity errors. (#1163)

[0.21.3] - 2023-09-28

Fixed

  • Pin CI conda channels (#1133)

  • Mangled kernel name generation (#1112)

Added

  • Support tests on single point precision GPUs (#1143)

  • Initial work on Coverity scan CI (#1128)

  • Python 3.11 support (#1123)

  • Security policy (#1117)

  • scikit-build to build native extensions (#1107, #1116, #1127, #1139, #1140)

Changed

  • Rename helper function to clearly indicate its usage (#1145)

  • The data model used by the DpnpNdArray type for kernel functions(#1118)

Removed

  • Support for Python 3.8 (#1113)

[0.21.2] - 2023-08-07

Fixed

  • Bugs (#1068, #774) in atomic addition caused due to improper floating point atomic emulation. (#1103)

Changed

  • Updated documentation and user guides (#1097, #879)

Removed

  • Dependency on spirv-tools (#1103, #1108)

  • floating point atomic add emulation using atomic_ops.cl (#1103)

  • NUMBA_DPEX_ACTIVATE_ATOMICS_FP_NATIVE configuration option (#1103)

[0.21.1] - 2023-07-17

Changed

  • Improved support for queue keyword in dpnp array constructor overloads (#1083)

  • Improved reduction kernel example (#1089)

Fixed

  • Update Itanium CXX ABI Mangler reference (#1080)

  • Update sourceware references in docstrings (#1081)

  • Typo in error messages of kernel interface (#1082)

[0.21.0] - 2023-06-17

Added

  • Support addition and multiplication-based prange reduction loops (#999)

  • Proper boxing, unboxing of dpctl.SyclQueue objects inside dpjit decorated functions (#963, #1064)

  • Support for queue keyword arguments inside dpnp array constructors in dpjit (#1032)

  • Overloads for dpnp array constructors: dpnp.full (#991), dpnp.full_like (#997)

  • Support for complex64 and complex128 types as kernel arguments and in parfors (#1033, #1035)

  • New config to run the ConstantSizeStaticLocalMemoryPass optionally (#999)

  • Support for Numba 0.57 (#1030, #1003, #1002)

  • Support for Python 3.11 (#1054)

  • Support for SPIRV 1.4 (#1056, #1060)

Changed

  • Parfor lowering happens using the kernel pipeline (#996)

  • Minimum required Numba version is now 0.57 (#1030)

  • Numba monkey patches are moved to numba_dpex.numba_patches (#1030)

  • Redesigned unit test suite (#1018, #1017, #1015, #1036, #1037, #1072)

Fixed

  • Fix stride computation when unboxing a dpnp array (#1023)

  • Using cached queue instead of creating new one on type inference (#946)

  • Fixed bug in reduction mul operation for dpjit (#1048)

  • Offload of parfor nodes to OpenCL UHD GPU devices (#1074)

Removed

  • Support for offloading NumPy-based parfor nodes to SYCL devices (#1041)

  • Removed rename_numpy_functions_pass (#1041)

  • Dpnp overloads using stubs (#1041, #1025)

  • Support for like keyword argument in dpnp array constructor overloads (#1043)

  • Support for NumPy arrays as kernel arguments (#1049)

  • Kernel argument access specifiers (#1049)

  • Support for dpctl.device_context to launch kernels and njit offloading (#1041)

[0.20.1] - 2023-04-07

Added

  • Replaced llvm_spirv from oneAPI path by dpcpp-llvm-spirv package.(#979)

  • Added Dockerfile and a manual workflow to publish pre-built packages to the repo.(#973)

Fixed

  • Fixed default dtype derivation when creating a dpnp.ndarray. (#993)

  • Adjusted test_windows step to work with intel-opencl-rt=2023.1.0. (#990)

  • Fixed layout in dpnp overload.(#987)

  • Handled the case when arraystruct->meminfo is null to close gh-965. (#972)

[0.20.0] - 2023-03-06

Added

  • New dpjit decorator supporting dpnp compilation (#887)

  • Boxing and unboxing functionality for dpnp.ndarray to numba_dpex (#902)

  • New DpexTarget and dispatcher for compiling dpnp using numba-dpex (#887)

  • Overload implementation for dpnp.empty (#902)

  • Overload implementation for dpnp.empty_like, dpnp.zeros_like and dpnp.ones_like inside dpjit (#928)

  • Overload implementation for dpnp.zeros and dpnp.ones inside dpjit (#923)

  • Compilation and offload support for dpnp vector style expressions using Numba parfors (#957)

  • Compilation of over 70 ufuncs for dpnp inside dpjit (#957)

  • Backported the split parfor pass from upstream Numba. (#949)

  • Numba type aliases to numba_dpex. (#851)

  • Numba prange alias inside numba_dpex. (#957)

  • New LRU cache for kernels (#804) and funcs (#877)

  • New Range and NdRange classes for kernel submission that follow sycl’s range and ndrange syntax. (#888)

  • Monkey pacthes to Numba 0.56.4 to support dpnp ufuncs, allocating dpnp arrays (#954)

  • New config flag (NUMBA_DPEX_DUMP_KERNEL_LLVM) to dump a kernel’s LLVM IR (#924)

  • A badge to our gitter chatroom (#919)

  • A small script to update copyright headers (#917)

  • A new dpexrt_python extension to support USM allocators for Numba NRT_MemInfo (#902)

  • Updated examples for kernel API demonstrating compute-follows-data programming model. (#826)

Changed

  • CLK_GLOBAL_MEM_FENCE and CLK_LOCAL_MEM_FENCE flags renamed to GLOBAL_MEM_FENCE and LOCAL_MEM_FENCE. (#844)

  • Switched from Ubuntu-latest to Ubuntu-20.04 for conda package build (#836)

  • Rename USMNdArrayType to USMNdArray (#851)

  • Changes to the Numba type to represent dpnp ndarray typess now renamed to DpnpNdarray (#880)

  • Improved exceptions and user errors (#804)

  • Updated internal API for kernel interface with improved support for __sycl_usm_array_interface__ protocol (#804)

  • Pin generated spirv version for kernels to 1.1 (#885)

  • Rename DpexContext and DpexTypingContext to DpexKernelTarget and DpexKernelTypingContext (#887)

  • Renamed existing dpnp overloads that used stubs to dpnp_stubs_impl.py (#953)

  • Dpctl version requirement mismatch is now a warning and not an ImportError (#925)

  • Update to versioneer 0.28 (#827)

  • Update to dpctl 0.14 (#858)

  • Update linters: black to 23.1.0, isort to 5.12.0 (#900)

  • License in setup.py to match actual project licensing (#904)

Fixed

  • Kernel specialization, compute follows data programming model for kernels (#804)

  • Dispatcher/caching rewrite to address performance regression (#912, #896)

  • func decorator qualname ambiguation fix (#905)

Removed

  • Removes the numpy_usm_shared module from numba_dpex. (#841)

  • Removes the usage of llvmlite.llvmpy (#932)

Deprecated

  • Support for NumPy arrays as kernel arguments (#804)

  • Kernel argument access specifiers (#804)

  • Support for dpctl.device_context to launch kernels and njit offloading (#804)

  • Dpnp overloads using stubs. (#953)

[0.19.0] - 2022-11-21

Added

  • Supported numba0.56. (#818)

  • Supported dpnp0.11 and dpctl0.14.

  • Added customized exception classes. (#798)

Fixed

  • Fixed a crash when calling take() for input array with non-integer values. (#771)

  • Fixed pairwise_distance.py to run on machine with no FP64 support in HW. (#806)

[0.18.1] - 2022-08-06

Added

  • Implemented support for dpnp.empty() (#728)

Changed

  • numba-dppy package is now renamed to numba-dpex.

[0.18.0] - 2022-02-22

Added

  • Run coverage in GitHub Actions and upload results to coveralls.io (#621)

  • Change black to only allow 80 char lines. Reformat sources. (#631)

  • Ignore formatting changes from git-blame. (#632)

  • Add numba_support.py with numba_version (#656)

  • Add skip_no_numba055 decorator (#662)

  • Parameterize test for atomics (#661)

  • Reuse decorator skip_no_opencl_Xpu to skip tests (#663)

  • Add decorator to skip unsupported atomics (#664)

  • Support arrays with __sycl_usm_array_interface__ attribute (#629)

  • Support memory allocation in private address space (#640)

  • Move skips for opencl to helper (#665)

  • Support dpctl 0.12 (#669)

  • Implement compute-follows-data programming model [kernel API] (#598)

  • Use filter_str to skip tests on missing devices (#672)

  • Add check for DPNP and pin MKL version in workflow and dev environment (#648)

  • Add CODEOWNERS for distributing review process (#670)

  • Add skip_no_dpnp and apply it to all tests (#668)

  • Test skipping improvements (#675)

  • Use Python 3.9 in dev environment and pin DPNP (#644)

  • Add examples into package (#680)

  • Make possible to force debugging tests (#681)

  • Refactoring for debugging tests (#682)

  • Adopt Numba 0.55 debugging features (#654)

  • Run public CI on pull request (#695)

  • Support for coverage in internal CI (#708)

  • Update to dpnp 0.10 (#709)

  • Update recipe with dpctl and dpnp version for build (#710)

Changed

  • Move dpcpp/llvm-spirv from runtime to testing dependency (#659)

Fixed

  • Fix building with DPNP (#674)

  • Fix public CI: opencl driver, channel priority, dpctl version (#691)

  • Fix codestyle black (#696)

  • Fix documentation generation (#697)

  • Load dpctl lib on Linux using libDPCTLSyclInterface.so.0 (#707)

  • Fix search llvm-spirv if dpcpp compiler package is not installed (#703)

  • Pin dpnp version in runtime to allow dev versions of dpnp (#712)

[0.17.4] - 2021-12-02

Changed

  • Move dpcpp/llvm-spirv from runtime to testing dependency by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/659

[0.17.3] - 2021-11-30

Changed

  • Use llvm-spirv from dpcpp compiler package by default [cherry picked from #649] (#651)

Fixed

  • Enable offloading for numba.njit in dpctl.deveice_context (#630)

  • Fix upload conditions for main and release branches (#610)

  • Fix DeprecationWarning when use version.parse() [cherry picked from #639] (#642)

[0.17.2] - 2021-11-15

Changed

  • Use llvm-spirv from bin-llvm during build for Linux and Windows (#626, #627)

[0.17.1] - 2021-11-10

Changed

  • Update clang to icx (#622)

[0.17.0] - 2021-11-03

Added

  • Use Python 3.9 [public CI] by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/574

  • Use NUMBA_DPPY_DEBUG for debugging GDB tests by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/578

  • Preliminary support Numba 0.55 (master branch) by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/583

  • Workflow for manually running tests using Numba PRs by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/586

  • Add public CI trigger on tags by @1e-to in https://github.com/IntelPython/numba-dppy/pull/589

  • Upload packages for release* branches by @1e-to in https://github.com/IntelPython/numba-dppy/pull/593

  • Update to dpctl 0.11 by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/595

  • Update to dpnp 0.9 by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/599

  • Improve the documenatation landing page by @diptorupd in https://github.com/IntelPython/numba-dppy/pull/601

  • Clean up README by @diptorupd in https://github.com/IntelPython/numba-dppy/pull/604

Fixed

  • Restrict dpctl to 0.10.* for release 0.16 by @1e-to in https://github.com/IntelPython/numba-dppy/pull/590

  • Fix upload from release branch by @1e-to in https://github.com/IntelPython/numba-dppy/pull/596

  • Unskip tests passing with dpnp 0.9.0rc1 by @PokhodenkoSA in https://github.com/IntelPython/numba-dppy/pull/606

[0.16.1] - 2021-10-20

Changed

  • Fix dpctl to 0.10 (#590)

  • Add Public CI trigger for tags (#589)

[0.16.0] - 2021-09-28

Added

  • Improve build and infra scripts (#544)

  • Add docs about local variables lifetime (#534)

  • Public CI for Windows (#536, #558)

  • Add info about tags in documentation (#543)

  • Add code coverage configurations (#561)

  • Add support pytest-cov and pytest-xdist (#562)

  • Add documentation workflow (#547)

  • Test numba and numba-dppy API with GDB (#566)

  • Transform commands scripts for GDB to tests (#568)

Changed

  • Update dpnp 0.8 (#524)

  • Fix passing strides array to DPNP dot and matmul (#565)

  • Use older compiler for backwards compatibility (#549)

  • Update conda recipe dependency for dpnp (#535)

  • Update dpctl 0.10 (memcpy async) (#529)

  • Change channels priority in public CI (#532)

  • Added runtime dependency llvm-spirv 11.* (#523)

  • Update test matrix in README (#560)

  • Use dpctl 0.10* and dpnp 0.8* in development configuration (environment.yml)

Fixed

  • Update test and fix typo for atomics (#550)

  • Delete unused file run_test.sh

  • Fix Public CI for using development packages (#522)

  • Removed redundant import in docs (#521)

[0.15.0] - 2021-08-25

Added

  • Introduce array ultilites to check, allocate and copy memory using SYCL USM (#489)

  • Add packaging in run dependencies (#505)

  • Add skipping tests for run without GPU (#508)

  • Add CI pipeline on GitHub Actions for Linux (#507)

  • Enable dpctl.tensor.usm_ndarray for @dppy.kernel (#509)

  • Enable @vectorize for target dppy (#497)

  • Add integration channels to GitHub Actions and make workflow consistent with dpctl (#510)

Changed

  • Update to Numba 0.54.0 (#493)

  • Update to dpctl 0.9 (#514)

  • Update to dpnp 0.7 (#513)

  • Use dpcpp compiler package for Linux (#502)

  • Update go version (#515)

Removed

  • Remove llvmdev from runtime dependecies (#498)

Fixed

  • Fix required compiler flags for processing genreated DWARF symbols (#500)

[0.14.4] - 2021-07-09

Fixed

  • Fix emission of debug information (#424)

  • Fix examples demonstrating GDB usage on a numba_dppy.kernel function. (#455)

  • Remove address space cast from global to generic inside numba_dppy.kernel (#432)

  • Fix debugging of local variables (#432)

  • Assert offload to SYCL devices in tests (#466)

  • Removed calling opt to convert LLVM IR to LLVM Bitcode (#481)

Added

  • Add examples for debugging (#426)

  • Added a new NUMBA_DPPY_DEBUGINFO environment variable to control GDB usage (#460)

  • Add debug option to dppy.kernel decorator (#424)

  • Enable debugging of nested GPU functions (#424)

  • Enable setting breakpoints by function names while Debugging (#434)

  • Various fixes and improvements to documentation about debugging (#479, #474, #475, #480, #475, #477, #468,#450)

  • Add automatic generation of commands for debugging (#463)

  • Add tests on debugging local variables (#421)

  • Enable eager compilation of numba_dppy.kernel (#291)

  • Increase test coverage for native atomic ops (#435)

  • Check and deter users from returning values from numba_dppy.kernel (#476)

[0.14.3] - 2021-05-27

Fixed

  • Add check for ONEAPI_ROOT dir (#411)

  • Fix using unquoted environment variable for clang path (#386)

  • Fix kernel caching (#408)

[0.14.2] - 2021-05-26

Added

  • Update documentation: version 0.14 (#378), API docs (#388), note about Intel Python Numba (#389),

  • Update User Guides about Debugging (#380), recommendations (#323), locals (#394), stepping (#400), configure environment (#402), set up machine (#396), info functions (#405)

  • Update Developer Guides about DPNP integration (#362)

  • Update README: add link to docs (#379), add Cython and pytest in dependencies, add test matrix (#305)

  • Add initial integration testing with dpnp and usm_ndarray (#403)

  • Introduce type in Numba-dppy to represent dpctl.tensor.usm_ndarray (#391)

  • Improve error reporting when searching for dpctl. (#368)

  • Enable Python 3.8 in CI (#359)

  • Adds a new utils submodule to provide LLVM IR builder helpers. (#355)

  • Improve warning and error messages when parfor offload fails. (#353)

  • Extend itanium mangler to support numba.types.CPointer and add test (#339)

  • Enable optimization level setting (#62)

  • Improve message printed during parfor lowering. (#337)

  • Initial tests for debug info (#297)

  • Add Bandit checks (#264)

Changed

  • Update to dpctl 0.8 (#375)

  • Update to Numba 0.53 (#279), inluding override get_ufunc_info in DPPYTargetContext (#367)

  • Update to DPNP 0.6 (#359)

  • Refactor test function generation (#374)

  • Ignore the cython generated cpp files inside dpnp_glue. (#351)

  • Add automerge main to gold/2021 (#349)

  • Fix dpnp version restriction in conda recipe (#347)

  • Change all Numba-dppy examples to work wih dpctl 0.7.0 (#309)

  • Restrict dpnp version (#344)

  • Feature changes related to dpctl 0.7 (#340)

  • Rename dpNP to dpnp (#334)

  • Ignore generated spir files (#333)

  • Use correct names for other products dpctl, Numba, dpnp (#310)

  • Remove dead code only if function name is replaced (#303)

  • Update license in conda recipe (#350)

  • Update blackscholes examples (#377)

Fixed

  • Fix dppy_rt extension (#393)

  • Update SYCL Filter String (#390)

  • Fix atomics (#346)

  • Fixes memory leaks in the usage of dpctl C API functions. (#369)

  • Fix SPIR-V validation (#354)

  • Fix run pre-commit check on main branch

  • Fix tests to skip if device is not available (#345)

  • Make Test Matrix table smaller in README (#308)

  • Fix black action. (#306)

  • Fix “subprocess.check_call” for Windows (#269)

[0.13.1] - 2021-03-11

Fixed

  • Add spir file to package.

  • Do not modify CC env variable during build.

  • Use correct version in documentation.

[0.13.0] - 2021-03-02

Added

  • Documentation.

  • Add support for dpctl.dparray.

  • Support NumPy functions via DPNP: random, linalg, transcendental, array ops, array creation.

  • Wheels building.

  • Using Bandit for finding common security issues in Python code.

Changed

  • Start using black code style formatter.

  • Build SPIRV code in setup.py.

  • Start using pytest for running tests.

  • Start using Apache 2.0 license.

  • Consistency of file headers.

  • Updated to Numba 0.52, dpCtl 0.6 and dpNP 0.5.1.

  • Don’t create a new copy of a usm shared array data pointers for kernel call.

  • Modify test cases and examples to use Level Zero queue.

Fixed

  • Fix incorrect import in examples.

[0.12.0] - 2020-12-17

Added

  • numba-dppy is a standalone package now. Added setup.py and conda recipe.

  • Offload diagnostics.

  • Controllable fallback.

  • Add flags to generate debug symbols.

  • Implementation of np.linalg.eig, np.ndarray.sum, np.ndarray.max, np.ndarray.min, np.ndarray.mean.

  • Two new re-write passes to convert NumPy calls into a pseudo numba_dppy call site to allow target-specific overload of NumPy functions. The rewrite passes is a temporary fix till Numba gains support for target-specific overlaods.

  • Updated to dpCtl 0.5.* and dpNP 0.4.*

Changed

  • The dpnp interface now uses Numba’s @overload functionality as opposed to the previous @lower_builtin method.

  • Rename DPPL to DPPY.

  • Cleaned test code.

  • DPPLTestCase replaced with unittest.TestCase.

  • All tests and examples use with device_context.

  • Config environment variables starts with NUMBA_DPPY_ (i.e. NUMBA_DPPY_SAVE_IR_FILES and NUMBA_DPPY_SPIRV_VAL)

  • Remove nested folder dppl in tests.

  • No dependency on cffi.

Removed

  • The old backup file.

NUMBA Version 0.48.0 + DPPY Version 0.3.0 (June 29, 2020)

This release includes:

  • Caching of dppy.kernels which will improve performance.

  • Addition of support for Intel Advisor which will help in profiling applications.