The Matrix Foundation has released patches and mitigation details for two vulnerabilities that use its open standard communications protocol to transmit sensitive information. The nonprofit Matrix ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

The C programming language is one of the most influential in computing history. In just 100 seconds, learn why C remains the backbone of modern software—powering operating systems like Linux, Windows, ...

Projects from the Parallel and Concurrent Programming course cover core topics like matrix operations, synchronization, and force calculations. Using MPI for process management, these assignments ...

Abstract: Vector-matrix multiplication dominates the computation time and energy for many workloads, particularly neural network algorithms and linear transforms (e.g, the Discrete Fourier Transform).

Provide Purdue faculty, staff, and students with a single source summary of URE programs. Give UR programs, administrators, and mentors broader and inclusive marketing to prospective student ...

Most neural network topologies heavily rely on matrix multiplication (MatMul), primarily because it is essential to many basic processes. Vector-matrix multiplication (VMM) is commonly used by dense ...

Is there any way to perform batched matrix multiplication within a program instance? For example, within a program I might load two tensors with shapes (8, 16, 16) and (8, 16, 16). The batch size is 8 ...

Drew Goddard, the Oscar-nominated screenwriter of The Martian who also directed The Cabin in the Woods, has been set to write and direct a new Matrix movie at Warner Bros. The franchise’s original ...

Computer scientists are a demanding bunch. For them, it’s not enough to get the right answer to a problem — the goal, almost always, is to get the answer as efficiently as possible. Take the act of ...