VaLVe: A programmer productivity tool

MulticoreWare presents VaLVe, a cutting-edge solution crafted to ensure seamless compatibility with ARM V9 and RISC-V architectures. At its core, VaLVe boasts a versatile vector intrinsic layer capable of supplanting SVE or RVV intrinsics coupled with a potent C++ vector productivity library. This powerful combination empowers developers to harness the full potential of variable-length vectors, ushering in a new era of portability, performance, and cost-efficiency in application development.

Navigating the Complexity of Variable-Length Vectors

In the ever-evolving landscape of computing, creating applications that prioritize performance while managing the cost implications of implementing variable-length vectors presents a formidable challenge. VaLVe takes on this challenge head-on by providing a comprehensive solution. It offers a C/C++ environment that allows developers to write code once and compile it repeatedly, ensuring compatibility across a diverse range of architectures.

Seamless Portability Across Architectures

MulticoreWare’s expertise spans various SIMD instruction sets, including MMX, SSE2, AVX, and AVX-512, originating from x86 and earlier RISC architectures. With VaLVe, applications initially developed in C/C++ for 64-bit processors can smoothly transition to new architectures supporting Variable Length Vectors, including SVE/SVE2 and their equivalents. The VaLVe C and VaLVe C++ library toolset leverages these vector instructions, vector registers, and vector memory features to simplify the migration process.

It introduces an architecture-independent VLV C Portability Layer and an intuitive vector programming syntax validator in the form of the VLV C++ Productivity Layer. This dynamic duo streamlines porting, making it quicker, simpler, and future-proof, regardless of changes to SIMD scalable instruction sets. VaLVe serves as the bridge that empowers developers to navigate the ever-changing landscape of 64-bit CPU architectures, optimizing both programmer productivity and application efficiency with finesse.

Heterogeneous Compute Compilers (HCC)

Neural Network Optimization Engines

Domain Specific languages

Hardware Platforms


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