TOPS per Watt or Tera Operations Per Second per Watt – a (less than perfect) measure of the efficiency of AI hardware.
When comparing the performance of AI hardware using TOPS per Watt, it is important to take into account the differences between hardware variants that work in floating point versus those that quantize data. Here are some pros and cons of using TOPS per Watt in this context:
Pros:
- Energy efficiency: Even when comparing hardware that uses different data types, TOPS per Watt can provide a useful measure of the energy efficiency of the hardware.
- Fair comparison: TOPS per Watt provides a way to compare the performance of hardware that uses different data types on an equal footing, by taking into account the amount of energy used to perform a given number of operations.
- Simplified analysis: Using TOPS per Watt as a metric can simplify the analysis of hardware performance, by providing a single number that takes into account both performance and energy efficiency.
Cons:
- Different data types: The use of different data types can affect the accuracy and speed of AI models, which can impact the performance of the hardware. Therefore, using TOPS per Watt alone may not provide a complete picture of the hardware’s performance.
- Limited scope: TOPS per Watt is just one metric to measure the performance of AI hardware. It does not take into account other factors such as memory bandwidth, latency, and parallel processing capability, which can also affect the performance of the hardware.
- Variations in implementation: Different vendors may implement quantization differently, making it difficult to compare the performance of different hardware platforms accurately.