\part{Scalable Vectors Primer}
-\chapter{Executive Summary}
\input{svp64-primer/acronyms}
+\chapter*{Executive Summary}
\include{svp64-primer/summary}
\bibliography{svp64-primer/references}
\bibliographystyle{ieeetr}
-\section{Summary}
+\section*{Summary}
The proposed \acs{SV} is a Scalable Vector Specification for a hardware for-loop \textbf{that
ONLY uses scalar instructions}.
\pagebreak
-\subsection{What is SIMD?}
+\subsection*{What is SIMD?}
\acs{SIMD} is a way of partitioning existing \acs{CPU}
registers of 64-bit length into smaller 8-, 16-, 32-bit pieces.
\textit{As long as the data width fits the workload, everything is fine}.
\par
-\subsection{Shortfalls of SIMD}
+\subsection*{Shortfalls of SIMD}
SIMD registers are of a fixed length and thus to achieve greater
performance, CPU architects typically increase the width of registers
(to 128-, 256-, 512-bit etc) for more partitions.\par Additionally,
Multi-issue decoding
\end{itemize}
-\subsection{Scalable Vector Architectures}
+\subsection*{Scalable Vector Architectures}
An older alternative exists to utilise data parallelism - vector
architectures. Vector CPUs collect operands from the main memory, and
store them in large, sequential vector registers.\par
\pagebreak
-\subsection{Simple Vectorisation}
+\subsection*{Simple Vectorisation}
\acs{SV} is a Scalable Vector ISA designed for hybrid workloads (CPU, GPU,
VPU, 3D). Includes features normally found only on Cray-style Supercomputers
(Cray-1, NEC SX-Aurora) and GPUs. Keeps to a strict uniform RISC paradigm,