Build AI accelerators and data center processors with RISC-V by learning how open architecture, vector extensions, neural processing, and server-grade system design come together in real AI and high-performance computing environments. RISC-V is no longer just a niche architecture for experimentation, but understanding where it fits in AI and HPC can still feel fragmented and overly technical. You need a clear view of the hardware, software stack, performance tradeoffs, and deployment realities before you can make informed decisions. This book gives you a practical, grounded guide to RISC-V for modern AI and high-performance computing. It explains the architecture, toolchains, and system design choices that matter, then connects them to real workloads, from vectorized kernels and AI frameworks to clusters, cloud integration, and production planning. What readers will learn: • Where RISC-V fits in AI accelerators, servers, edge systems, and supercomputers • How RV64GC, RVA23, privileged architecture, virtual memory, and atomics affect real systems • How to use RVV for AI and scientific computing, including vector-length-agnostic programming • How packed SIMD, low-precision formats, crypto, and bit manipulation support modern workloads • How server-grade and manycore RISC-V microarchitectures are designed for AI and HPC • How to work with Linux, GCC, LLVM, profiling tools, debuggers, and simulators on RISC-V • How AI software stacks, ML compilers, BLAS libraries, and frameworks such as llama.cpp run on RISC-V • How HPC software, MPI, OpenMP, virtualization, containers, and cloud-native stacks fit into the ecosystem • How to select ISA extensions, cores, and accelerators for a target workload • How to co-design hardware and software, build practical clusters, and evaluate roadmap risks before production adoption The book also includes decision checklists for adopting RISC-V in production systems, helping you think through architecture choices, deployment tradeoffs, and workload fit with more confidence. This is a code-heavy guide with working examples in C, C++, assembly, shell, and YAML that help you apply the concepts to kernel development, toolchain setup, vector programming, and practical system deployment. If you want a clear, practical introduction to using RISC-V for AI and high-performance computing, this book will help you understand the platform, work with the software stack, and plan real-world systems with greater clarity.
