# Recent Developments in Low-Power AI Accelerators: A Survey
## 3 Method
### Missing Data  
Since there exist no standards on what information should exist in both research papers and company briefs for AI accelerators, a few metrics and measurements are missing from the gathered information regarding different AI accelerators in our survey, e.g., power, throughput, power efficiency, etc.  
There are times when this could be rectified. In the data gathered from the surveyed accelerators, we are able to compute some of these missing values. Throughput, or operations per second, can be calculated with Equation (2).  
\[Throughput=\#MACs\times Frequency=\#MACs\times\frac{Cycles}{Second}, \tag{2}\]  
where \(\#MACs\) is the number of MAC components in the accelerator (often calculated from the number of PEs used and their internal components), \(Frequency\) is the frequency in Hz, and \(Throughput\) is the number of operations per second, often translated to Giga Operations per Second (GOPS) or Tera Operations per Second (TOPS). A similar approach is used for calculating the throughput used in SNN accelerators, where Giga-synaptic Operations per Second (GSyOPS) is often preferred.  
If power is missing, we can calculate it by using Equation (3).  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Targets** & \multicolumn{2}{c}{**2019**} & \multicolumn{2}{c}{**2020**} & \multicolumn{2}{c}{**2021**} & \multicolumn{2}{c}{**2022**} \\ \hline  & **Research** & **Company** & **Research** & **Company** & **Research** & **Company** & **Research** & **Company** \\ \hline CNN & 10 & 4 & 5 & 4 & 7 & 6 & 2 & - \\ GAN & 1 & - & 1 & - & 1 & - & 1 & - \\ DNN & 2 & 3 & 4 & - & 2 & 5 & 1 & - \\ Transformer & 1 & - & 1 & - & 3 & 2 & 3 & - \\ SpGEMM & 1 & - & 2 & - & 1 & - & - & - \\ SNN & 1 & - & 3 & - & 2 & - & 2 & - \\ ANN & 1 & - & 1 & - & - & - & - & - \\ RNN & 2 & - & - & 4 & 1 & 3 & 1 & - \\ LSTM & 1 & 1 & - & 4 & - & 3 & - & - \\ PR system & - & - & 1 & - & - & - & - & - \\ GEMM & - & - & 2 & - & 3 & - & 1 & - \\ MAC & - & - & 1 & - & - & - & - & - \\ Matrix Alg. & - & - & 1 & - & - & - & - & - \\ MLP & - & - & - & - & 1 & - & - & - \\ Graph Mining & - & - & - & - & - & - & 2 & - \\ SpMatrix Transposition & - & - & - & - & - & - & 1 & - \\ Attention & - & - & - & - & - & - & 1 & - \\ \hline
**Unique targets** & 9 & 3 & 11 & 3 & 9 & 5 & 10 & 0 \\ \hline
**Total targets** & 19 & 8 & 22 & 12 & 21 & 19 & 15 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Number of acceleration targets per year. Divided into company and non-company (research) acceleration targets. Note that an accelerator can accelerate more than one target.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **2019** & **2020** & **2021** & **2022** \\ \hline
**Company** & 6 & 4 & 8 & 0 \\
**Academia** & 16 & 17 & 16 & 12 \\ \hline
**Total** & 22 & 21 & 24 & 12 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Number of accelerators per year. Divided into company and non-company (research) accelerators.  
\[Power=\frac{Energy}{Cycle}\times Frequency=\frac{Energy}{Cycle}\times\frac{Cycles}{ Second}, \tag{3}\]  
where the _Energy_ of each component of the accelerator (if mentioned) is measured in \(J\) per cycle (operation). The frequency is measured in Hz, i.e., \(cycles/s\), and the result is _Power_, measured in \(J/s=\) W.  
We can calculate power efficiency (GOPS/W) if both throughput and power are mentioned or if they can be calculated. This is done by dividing the throughput with the power. Area efficiency is calculated in a similar fashion.