Abstract: This paper investigates the impact of loop unrolling on CUDA matrix multiplication operations’ performance across NVIDIA GPUs. We benchmarked both basic and unrolled kernels with varying ...

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Abstract: Machine Learning and AI approaches have stretched traditional hardware to its limits. In-hardware computing is a novel approach that aims to run Matrix-Vector Multiplication operations ...

If the mention of algebra conjures bad memories of math classes, a Python library called SymPy could change your mind about the subject. With SymPy, algebraic operations become easier than tedious ...

The UC Berkeley crew has now shown the value of AI-based optimization work by having OpenEvolve work out a more efficient approach to load balancing across GPUs handling LLM inference.

Using embedded-array programmable logic, it's possible to build multipliers that run faster than previous programmable-logic implementations. With the method shown here, you can make 4×4 multipliers ...

The one chip startup building accelerators for something other than AI boasts performance up 10x that of modern GPUs using a ...

The WIAA has a new playoff qualification system for high school football starting in 2025. Playoff spots are no longer guaranteed by conference wins but by a new points-based matrix. A team's score is ...

To get this project up and running locally, follow these steps. The following Go functions are exposed via FFI and can be called from Python and Node.js using the generated bindings.