[Project] Release 1.1.0

Author: EgorOrachyov

CHANGELOG.md

@@ -0,0 +1,56 @@
+# Changelog
+
+All notable changes to this project are documented in this file.
+Changes format: version name and date, minor notes, new features, fixes, what removed.
+
+Release are available at [link](https://github.com/JetBrains-Research/cuBool/releases). 
+
+## v1.1.0 - May 8, 2021
+
+### Summary
+
+Introduce sparse vector of boolean values support for Cuda and CPU computations.
+Added new primitive type as well as supported common operations,
+which involve matrix-vector operations and vector manipulation.
+Added new vector C API, exposed vector primitive into python-package.
+
+#### New features
+
+- Sparse vector support
+- Vector implementation for Cuda backend
+- Vector implementation for Sequential backend
+- Vector creation (empty, from data, with random data)
+- Matrix-vector operations (matrix-vector and vector-matrix multiplication)
+- Vector-vector operations (element-wise addition)
+- Matrix operations (equality, reduce to value, extract sub-vector)
+- Vector data extraction (as list of indices)
+- Vector syntax sugar (pretty string printing, slicing, iterating through non-zero indices)
+- Matrix operations (extract row or matrix column as sparse vector, reduce matrix (optionally transposed) to vector)
+
+#### Deprecated
+
+- Matrix reduce to matrix (compatibility feature)
+
+## v1.0.0 - Apr 2, 2021
+
+### Summary 
+
+cuBool is a sparse linear Boolean algebra for Nvidia Cuda computations. 
+Library provides C compatible API, the core of the library is written on C++ with CUDA C/C++ API and 
+Thrust for Cuda related computations. Library also supports CPU backend for non-Cuda devices. 
+pycubool Python-package is shipped with the library source code and it provides high-level safe 
+and efficient access to the library within Python runtime.
+
+#### New features
+
+- Cuda backend
+- Sequential (CPU) backend
+- Sparse matrix support
+- Matrix creation (empty, from data, with random data)
+- Matrix-matrix operations (multiplication, element-wise addition, kronecker product)
+- Matrix operations (equality, transpose, reduce to vector, extract sub-matrix)
+- Matrix data extraction (as lists, as list of pairs)
+- Matrix syntax sugar (pretty string printing, slicing, iterating through non-zero values)
+- IO (import/export matrix from/to .mtx file format)
+- GraphViz (export single matrix or set of matrices as a graph with custom color and label settings)
+- Debug (matrix string debug markers, logging, operations time profiling)

README.md

@@ -5,7 +5,7 @@
 [![JB Research](https://jb.gg/badges/research-flat-square.svg)](https://research.jetbrains.org/)
 [![Ubuntu](https://github.com/JetBrains-Research/cuBool/workflows/Ubuntu/badge.svg?branch=master)](https://github.com/JetBrains-Research/cuBool/actions)
 [![License](https://img.shields.io/badge/license-MIT-orange)](https://github.com/JetBrains-Research/cuBool/blob/master/LICENSE)
-[![Package](https://img.shields.io/badge/pypi%20package-1.0.0-%233776ab)](https://pypi.org/project/pycubool/)
+[![Package](https://img.shields.io/badge/pypi%20package-1.1.0-%233776ab)](https://pypi.org/project/pycubool/)
 
 **cuBool** is a linear Boolean algebra library primitives and operations for 
 work with sparse matrices written on the NVIDIA CUDA platform. The primary 
@@ -327,18 +327,17 @@ cuBool
 @MISC{cuBool,
   author = {Orachyov, Egor and Alimov, Pavel and Grigorev, Semyon},
   title = {cuBool: sparse Boolean linear algebra for Nvidia Cuda},
-  year = 2020,
+  year = 2021,
   url = {https://github.com/JetBrains-Research/cuBool},
-  note = {Version 1.0.0}
+  note = {Version 1.1.0}
 }
 ```
 
 ## Algorithms
 
-In this section listed all the related papers, articles and links, which
-were used as an algorithmic foundation for implementation of sparse linear
-boolean algebra operations (sparse matrix-matrix multiplication, sparse matrix-vector
-multiplication, sparse vector-matrix multiplication, matrix-matrix element-wise addition and etc.):
+In this section listed all the related papers, which were used as an algorithmic foundation for 
+implementation of sparse linear boolean algebra operations (sparse matrix-matrix multiplication, 
+sparse matrix-vector multiplication, sparse vector-matrix multiplication, matrix-matrix element-wise addition and etc.):
 
 - High-performance and Memory-saving Sparse General Matrix-Matrix Multiplication for NVIDIA Pascal GPU, 
 Yusuke Nagasaka, Akira Nukada, Satoshi Matsuoka

cubool/CMakeLists.txt

@@ -140,7 +140,7 @@ if (CUBOOL_WITH_CUDA)
         sources/cuda/kernels/slow_sort.cuh
         sources/cuda/kernels/bin_search.cuh
         sources/cuda/kernels/spgemv.cuh
-            sources/cuda/kernels/spgemv_t.cuh
+        sources/cuda/kernels/spgemv_t.cuh
         sources/cuda/kernels/spewiseadd.cuh
         sources/cuda/kernels/sptranspose.cuh
         sources/cuda/kernels/sptranspose2.cuh

python/README.md

@@ -154,9 +154,9 @@ Script can be rendered by any [gviz tool](https://dreampuf.github.io/GraphvizOnl
 @MISC{cuBool,
   author = {Orachyov, Egor and Alimov, Pavel and Grigorev, Semyon},
   title = {cuBool: sparse Boolean linear algebra for Nvidia Cuda},
-  year = 2020,
+  year = 2021,
   url = {https://github.com/JetBrains-Research/cuBool},
-  note = {Version 1.0.0}
+  note = {Version 1.1.0}
 }
 ```
 

python/setup.py

@@ -20,11 +20,11 @@
 
 setuptools.setup(
     name="pycubool",
-    version="1.0.0",
+    version="1.1.0",
     author="Egor Orachyov",
     author_email="egororachyov@gmail.com",
     license="MIT",
-    description="cuBool library python bindings.",
+    description="cuBool library python bindings",
     long_description=README,
     long_description_content_type="text/markdown",
     url="https://github.com/JetBrains-Research/cuBool",