Artificial intelligence (AI) has become pervasive in our lives, improving our phones, cars, homes, medical centers, and more. As currently structured, these models primarily run in power-hungry, ...
Native Floating-Point HDL code generation allows you to generate VHDL or Verilog for floating-point implementation in hardware without the effort of fixed-point conversion. Native Floating-Point HDL ...
Infinite impulse response (IIR) filter implementations can have different forms (direct, standard, ladder, …), different math (fixed-point or floating-point), and different quantization (number of ...
AI/ML training traditionally has been performed using floating point data formats, primarily because that is what was available. But this usually isn’t a viable option for inference on the edge, where ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google today released Quantization Aware Training (QAT) API, which ...
Our whitepaper compares the efficiency of floating point and integer quantization. For training, the floating-point formats FP16 and FP32 are commonly used as they have high enough accuracy, and no ...
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