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Why Today¡¯s Vehicles Demand More Compute Power

Classification and processing of massive amounts of data from multiple sources in automotive applications ¨C video, audio, radar, lidar ¨C results in a high degree of complexity in automotive ICs as software algorithms require large amounts of compute power. Hardware architectural decisions, and even hardware-software partitioning, must be done with energy efficiency in mind. There is a plethora of tradeoffs at this stage:

• Flexibility of a general-purpose CPU-based architecture vs. efficiency of a dedicated digital signal processor (DSP) vs. a hardware accelerator
• Memory sub-system design: how much is required, how it will be partitioned, how much precision is really needed, just to name a few considerations

In order to enable reliable decisions, architects must have access to a system that models, in a robust manner, power, performance, and area (PPA) characteristics of the hardware, as well as use cases. The idea is to eliminate error-prone estimates and guesswork.

To improve energy efficiency, automotive IC designers also must adopt many of the power reduction techniques traditionally used by architects and engineers in the low-power application space (e.g. mobile or handheld devices), such as power domain shutoff, voltage and frequency scaling, and effective clock and data gating. These techniques can be best evaluated at the hardware design level (register transfer level, or RTL) ¨C but with the realistic system workload. As a system workload ¨C either a boot sequence or an application ¨C is millions of clock cycles long, only an emulation-based solution delivers a practical turnaround time (TAT) for power analysis at this stage. This power analysis can reveal intervals of wasted power ¨C power consumption bugs ¨C whether due to active clocks when the data stream is not active, redundant memory access when the address for the read operation doesn¡¯t change for many clock cycles (and/or when the address and data input don¡¯t change for the write operation over many cycles), or unnecessary data toggles while clocks are gated off.

To cope with the huge amount of data and the requirement to process that data in real time (or near real time), automotive designers employ artificial intelligence (AI) algorithms, both in software and in hardware. Millions of multiply-accumulate (MAC) operations per second and other arithmetic-intensive computations to process these algorithms give rise to a significant amount of wasted power due to glitches ¨C multiple signal transitions per clock cycle. At the RTL stage, with the advanced RTL power analysis tools available today, it is possible to measure the amount of wasted power due to glitches as well as to identify glitch sources. Equipped with this information, an RTL design engineer can modify their RTL source code to lower the glitch activity, reduce the size of the downstream logic, or both, to reduce power.

Working together with the RTL design engineer is another critical persona ¨C the verification engineer. In order to verify the functional behavior of the design, the verification engineer is no longer dealing just with the RTL source: they also have to verify the proper functionality of the global power reduction techniques such as power shutoff and voltage/frequency scaling. Doing so requires a holistic approach that leverages a comprehensive description of power intent, such as the Unified Power Format (UPF). All verification technologies ¨C static, formal, emulation, and simulation ¨C can then correctly interpret this power intent to form an effective verification methodology.

Power intent also carries through to the implementation part of the flow, as well as signoff. During the implementation process, power can be further optimized through physical design techniques while conforming to timing and area constraints. Highly accurate power signoff is then used to check conformance to power specifications before tape-out.