Processing with XSIMD About SIMD Data alignment Fixed-size chunks Separate builds for each CPU Compilation targets Multiarch builds 1. DLL-based approach 2. Template-based approach Explicit scalar implementation algorithm might be called for shorter chunks (e.g. for 10 pixels) Separate builds for each CPU Compilation targets The term “cpu optimization” is usually rather confusing. It can be used in three different scalar version is used used in the following cases: no XSIMD library is not found during the compilation of Krita the CPU Krita runs on doesn’t support any SIMD we know the user emplicitly disabled

Processing with XSIMD About SIMD Data alignment Fixed-size chunks Separate builds for each CPU Compilation targets Multiarch builds 1. DLL-based approach 2. Template-based approach Explicit scalar implementation algorithm might be called for shorter chunks (e.g. for 10 pixels) Separate builds for each CPU Compilation targets The term “cpu optimization” is usually rather confusing. It can be used in three different scalar version is used used in the following cases: no XSIMD library is not found during the compilation of Krita the CPU Krita runs on doesn’t support any SIMD we know the user emplicitly disabled

Processing with XSIMD About SIMD Data alignment Fixed-size chunks Separate builds for each CPU Compilation targets Multiarch builds 1. DLL-based approach 2. Template-based approach Explicit scalar implementation algorithm might be called for shorter chunks (e.g. for 10 pixels) Separate builds for each CPU Compilation targets The term “cpu optimization” is usually rather confusing. It can be used in three different scalar version is used used in the following cases: no XSIMD library is not found during the compilation of Krita the CPU Krita runs on doesn’t support any SIMD we know the user emplicitly disabled

Processing with XSIMD About SIMD Data alignment Fixed-size chunks Separate builds for each CPU Compilation targets Multiarch builds 1. DLL-based approach 2. Template-based approach Explicit scalar implementation algorithm might be called for shorter chunks (e.g. for 10 pixels) Separate builds for each CPU Compilation targets The term "cpu optimization" is usually rather confusing. It can be used in three different scalar version is used used in the following cases: no XSIMD library is not found during the compilation of Krita the CPU Krita runs on doesn't support any SIMD we know the user emplicitly disabled

Processing with XSIMD About SIMD Data alignment Fixed-size chunks Separate builds for each CPU Compilation targets Multiarch builds 1. DLL-based approach 2. Template-based approach XSIMD Library Arithmetic algorithm might be called for shorter chunks (e.g. for 10 pixels) Separate builds for each CPU Compilation targets The term “cpu optimization” is usually rather confusing. It can be used in three different

Processing with XSIMD About SIMD Data alignment Fixed-size chunks Separate builds for each CPU Compilation targets Multiarch builds 1. DLL-based approach 2. Template-based approach XSIMD Library Arithmetic algorithm might be called for shorter chunks (e.g. for 10 pixels) Separate builds for each CPU Compilation targets The term “cpu optimization” is usually rather confusing. It can be used in three different

Processing with XSIMD About SIMD Data alignment Fixed-size chunks Separate builds for each CPU Compilation targets Multiarch builds 1. DLL-based approach 2. Template-based approach XSIMD Library Arithmetic algorithm might be called for shorter chunks (e.g. for 10 pixels) Separate builds for each CPU Compilation targets The term “cpu optimization” is usually rather confusing. It can be used in three different

C:\Home\Code\krita-build cmake Compile and install Krita Use an IDE to assist in compilation You may want to use an IDE for development purposes. KDevelop and QtCreator are suggested for

C:\Home\Code\krita-build cmake Compile and install Krita Use an IDE to assist in compilation You may want to use an IDE for development purposes. KDevelop and QtCreator are suggested for