New Linear-complexity Multiplication (L-Mul) algorithm claims it can reduce energy costs by 95% for element-wise tensor multiplications and 80% for dot products in large language models. It maintains ...

[Editor's note: For an intro to fixed-point math, see Fixed-Point DSP and Algorithm Implementation. For a comparison of fixed- and floating-point hardware, see Fixed vs. floating point: a surprisingly ...

Floating-point arithmetic can be expensive if you're using an integer-only processor. But floating-point values can be manipulated as integers, asa less expensive alternative. One advantage of using a ...

Replacing computationally complex floating-point tensor multiplication with the much simpler integer addition is 20 times more efficient. Together with incoming hardware improvements this promises ...

Radar, navigation and guidance systems process data that is acquired using arrays of sensors. The energy delta from sensor to sensor over time holds the key to information such as targets, position or ...

Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...