Parallel Computing Software Engineer

NextSilicon is a swiftly growing unicorn startup that is reimagining high-performance computing. Our pioneering coprocessor vastly accelerates supercomputers, driving them forward into a new generation. Our new software-defined hardware architecture enables HPC and AI to fulfill its promise of breakthroughs in all fields of advanced research.

We are looking for an experienced software engineer with a strong background in optimizing parallel frameworks to hardware runtime, who will join our Apps Frameworks group.

Requirements:

• 6+ years of software engineering experience working on low-level software for heterogeneous compute.
• MSc/BSc in Computer Science or other equivalent educational experience.
• 5+ years of advanced C++ experience, with excellent coding skills.
• 3+ years of parallel compute software acceleration coding experience, utilizing one or more of the following frameworks: OpenMP, Kokkos, CUDA, OpenCL, and/or HIP.
• Experience with compilers (RISC-V, ARM and/or x86 backends) : a big advantage.
• In-depth knowledge of processor architectures—such asCPUs (x86, ARM, RISC-V), GPUs, DSPs, or TCUs : an advantage.
• Hands-on experience working with common linear algebra accelerated libraries : BLAS, FFTW, Eigen, LAPACK : an advantage.
• Experience with Linux foundations : an advantage.
  
  

• Play a key role in defining the architecture for the NextSilicon parallel compute framework API, and how it will interact with other common parallel compute frameworks.
• Research common parallel compute frameworks implementations and suggest design and implementation concepts for accelerating them on NextSilicon hardware.
• Dive into linear algebra common libraries codebase and understand how to integrate them into the NextSilicon SDK with the aim of best utilizing NextSilicon hardware.
• Understand our full NextSilicon software stack end-to-end,and be able to identify performance bottlenecks and implement accelerated solutions.
• Work in close collaboration with cross-functional and multidisciplinary teams, including software, hardware, system, research, and apps engineering teams.