The project CINN is a machine learning compiler and executor for multiple hardware backends. It is designed to provide multiple layers of APIs to make tensor computation easier to define, faster to ...
This work presents sPyNNaker 4.0.0, the latest version of the software package for simulating PyNN-defined spiking neural networks (SNNs) on the SpiNNaker neuromorphic platform. Operations ...
OpenTPU is an open-source re-implementation of Google's Tensor Processing Unit (TPU) by the UC Santa Barbara ArchLab. The TPU is Google's custom ASIC for accelerating the inference phase of neural ...
Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current ...
Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform ...
The i7 supports the x86-64 instruction set architecture, a 64-bit extension of the 80×86 architecture. The i7 is an out-of-order execution processor that includes four cores. In this chapter, we focus ...
We present a perspective on the past contributions, current status, and future directions of compiler technology and make four main recommendations in support of a vibrant compiler field in the years ...
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