Abstract: Compute-in-memory (CIM) is a new computing paradigm that addresses the memory-wall problem in hardware accelerator design for deep learning. The input vector and weight matrix multiplication ...
Abstract: To solve the problem of the difficult and slow detection of small defects in magnetic flux leakage (MFL), we propose a fast MFL small defect detection network (FSDDNet). First, we introduce ...
# Generates a realistic synthetic operational log for a delivery fleet. # Produces the raw data that fluxPrepare ingests in Tutorial 04. # Output: a list with six data frames: # ops <- ...
Provides a ComputeBackend trait that abstracts all hardware-specific matrix operations. Every LARQL crate (inference, vindex) uses this trait — the caller never knows whether the operation runs on CPU ...
Simply put, compute power is the measure of how much work a computer chip can do and how fast it can do it — like horsepower in a car engine. Compute power is measured in FLOPS: floating-point ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results