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GPU acceleration is the default assumption for machine learning inference. But Intel’s AMX (Advanced Matrix Extensions) may close the gap. AMX is built into recent Xeon processors, which are available from Azure. Can they compete with similarly priced GPU-based machines for the Tessera pipeline?
In a previous post, I compared the ONNX Runtime with PyTorch on the CPU and GPU. In this post, I take this to the extreme to see if a CPU can outpace the NVIDIA L4 GPU.
The Tessera pipeline is written in Python. What would it take to have an OCaml version?
In addition to the post from last week covering BON in a Box and OCaml Functors, below are some additional notes.
Even though registers are a low-level CPU concept, having some knowledge aboutthem can help write faster code. Simply put, a CPU register is a storage for as...
Sometimes it can be useful to inspect the state of a TCP endpoint. Things suchas the current congestion window, the retransmission timeout (RTO), duplicateac...




