The use of reduced precision to improve performance metrics such as computation latency
and power consumption is a common practice in the embedded systems field. This practice …

Many classes of applications, both in the embedded and high performance domains, can
trade off the accuracy of the computed results for computation performance. One way to …

With the ever-increasing energy-efficiency requirements for the computing platforms at the
edge, precision tuning techniques highlight the possibility of improving the efficiency of …

In the near future, Exascale systems will need to bridge three technology gaps to achieve
high performance while remaining under tight power constraints: energy efficiency and …

Precision tuning trades accuracy for speed and energy savings, usually by reducing the data
width, or by switching from floating point to fixed point representations. However, comparing …

High-Level Synthesis (HLS) tools have revolutionized FPGA application development by
providing a more efficient and streamlined approach, significantly impacting digital design …

Reducing floating-point (FP) precision is used to trade the quality degradation of a numerical
program's output for performance, but this optimization coincides with type casting, whose …

Fixed-point arithmetic is a popular alternative to floating-point arithmetic on embedded
systems. Existing work on the verification of fixed-point programs relies on custom …

We present the concept of approximate intermittent computing and concretely demonstrate
its application. Intermittent computations stem from the erratic energy patterns caused by …

Mixed precision is an approximate computing technique that can be used to trade-off
computation accuracy for performance and/or energy. It can be applied to many error …