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Found 3 papers, 1 papers with code
LookupFFN: Making Transformers Compute-lite for CPU inference
While GPU clusters are the de facto choice for training large deep neural network (DNN) models today, several reasons including ease of workflow, security and cost have led to efforts investigating whether CPUs may be viable for inference in routine use in many sectors of the industry.
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
A popular strategy is the use of low bit-width integers to approximate the original entries in a matrix.
Open-source Hardware: Opportunities and Challenges
Innovation in hardware is slowing due to rising costs of chip design and diminishing benefits from Moore's law and Dennard scaling.
Hardware Architecture Computers and Society
