Google DeepMind today pulled the curtain back on AlphaEvolve, an artificial-intelligence agent that can invent brand-new computer algorithms — then put them straight to work inside the company's vast ...

Abstract: Sparse matrix-vector multiplication (SpMV) is a fundamental operation in machine learning, scientific computing, and graph algorithms. In this paper, we investigate the space, time, and ...

This project is a 24-core, 32-thread GPU designed for the Spartan-7 FPGA (xcs50-csga324-1). It is optimized for integer matrix multiplication and sprite copying to a frame buffer. The GPU employs a ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

This package contains a framework to instantiate flexible, performant GEMM (General Matrix Multiplication) kernels. You can use this framework to define your own GEMM kernels, or use one of the ...

Treatment with combinations of drugs carries great promise for personalized therapy for a variety of diseases. We have previously shown that synergistic combinations of cancer signaling inhibitors can ...

Richard Dedekind was a 19th-century mathematical giant, responsible for reshaping the field right down to its foundations. He was the first to give a rigorous definition of infinity; he also came up ...

Most of today’s quantum algorithms may not achieve practical speedups. Material science and chemistry have a huge potential and we hope more practical algorithms will be invented based on our ...

Abstract: The domain wall-magnetic tunnel junction (DW-MTJ) is a versatile device that can simultaneously store data and perform computations. These three-terminal devices are promising for digital ...

The Shor's algorithm can find solutions to the discrete logarithm problem on binary elliptic curves in polynomial time. A major challenge in implementing Shor's algorithm is the overhead of ...