Making floating point math highly efficient for AI hardware

We have made radical changes to floating point to make it as much as 16 percent more efficient than int8/32 math.

A floating point implementation that is more efficient than typical integer math but in which one can still do lots of interesting work is very ...

Sahand Sojoodi on LinkedIn: Making floating point math highly ...

Floating point hardware operations are cool again! It's amazing that large AI models (ie. lots of floating point numbers!) are making us ...

Floating-point arithmetic for AI inference — hit or miss? | Qualcomm

Our whitepaper compares the efficiency of floating point and integer quantization. For training, the floating-point formats FP16 and FP32 are ...

AI engineers claim new algorithm reduces AI power consumption by ...

2: Perform the necessary integer additions instead of direct floating point multiplication. Apparently, this reduces the computational overhead ...

Addition is All You Need for Energy-Efficient Language Models ...

Compared to 8-bit floating point multiplications, the proposed method achieves higher precision but consumes significantly less bit-level ...

Jeff Johnson on LinkedIn: Making floating point math highly efficient ...

Hardware research at FAIR: Making floating point more efficient than integer math My recent paper "Rethinking floating point for deep ...

Hardware Mathematics for Artificial Intelligence - Synopsys

Normalization is a large percentage of the logic that makes up a floating point adder, and if eliminated, it would give margin to hardware optimization. The ...

Will Floating Point 8 Solve AI/ML Overhead?

“Eight-bit floating-point (FP8) data types are being explored as a means to minimize hardware — both compute resources and memory — while ...

Why do we need floats for using neural networks? - AI Stack Exchange

As mentioned above hardware is continuously developing in the direction to work with IEEE floating point vector and matrix arithmetic, ...

AI Chips Must Get The Floating-Point Math Right - OneSpin Solutions

But, as argued in this paper, using floating-point numbers for weights representation may result in significantly more efficient hardware ...

Floating-Point Arithmetic for AI Inference - Hit or Miss?

Going down in the number of bits improves the efficiency of networks greatly, but the ease-of-use advantage disappears. For formats like INT8 ...

Floating points in deep learning: Understanding the basics - Medium

Huang, and T.-W. Chen, “All-You-Can-Fit 8-Bit flexible Floating-Point format for accurate and Memory-Efficient inference of deep neural networks ...

AI engineers claim new algorithm reduces AI power consumption by ...

... floating-point multiplication with integer addition to make AI processing more efficient ... Also, have they never heard of fixed point math?

1. Introduction — Mixed-Precision Arithmetic for AI

Indeed, many scientific applications use the universal IEEE 754 32-bit and 64-bit floating-point representations as the default implementation to deliver high ...

Python __slots__, making floating point highly efficient ...

Deep learning algorithms used in AI rely on an enormous amount of data that go through floating point arithmetic. As such, it is imperative to ...

Integer addition algorithm could reduce energy needs of AI by 95%

The new technique is basic—instead of using complex floating-point multiplication (FPM), the method uses integer addition. Apps use FPM to ...

Floating-Point Formats in the World of Machine Learning

Over the last two decades, compute-intensive artificial-intelligence (AI) tasks have promoted the use of custom hardware to efficiently drive ...

Rethinking floating point for deep learning

It is historically known to be up to 10× less energy efficient in hardware implementations than integer math [14]. Typical implementation is encumbered with ...

What is FP64, FP32, FP16? Defining Floating Point | Exxact Blog

FP32 is the default for all applications that don't need extreme accuracy, nor does it need to be extremely fast. FP32 is as accurate you can ...