Search Results for "neon"

...Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. The library is written in C/C++ and designed for maximum portability, efficiency, and performance, leveraging platform-specific instruction sets (e.g., NEON, AVX, SIMD) for optimized execution. It supports NHWC tensor layouts and allows flexible striding along the channel dimension to efficiently handle channel-split and concatenation operations without additional cost.

...The assembler itself isn't a separate tool, but rather a collection of C/C++ header files, which applications need to include directly in order to use. At present, Intel SSE/SSE2/SSE4 and AVX/AVX2/AVX-512 (32/64-bit x86 ISAs), ARMv7 NEON/NEONv2, ARMv8 AArch32 and AArch64 NEON, SVE (32/64-bit ARM ISAs), MIPS 32/64-bit r5/r6 MSA and POWER 32/64-bit VMX/VSX (little/big-endian ISAs) are mostly implemented (/w horizontal reductions) although scalar improvements, wider SIMD vectors with zeroing/merging predicates in 3/4-operand instructions are planned as extensions to current 2/3-operand SPMD-driven vertical SIMD ISA. ...

libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, NEON, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, ARM, and PowerPC systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines.

This library is being created as I have a need to do very fast FFTs on low end devices not supporting the NEON instruction set. The Raspberry Pi is an ideal candidate for developing in gcc before porting to JNI for low spec Android devices, hence it's inclusion. Fixed point 16/32 integer FFT library suitable for the Raspberry Pi and Android devices. Includes test stubs for gcc on the Raspberry Pi and a Basic4Android wrapper from JNI.