Hopper (microarchitecture)Hopper is a graphics processing unit (GPU) microarchitecture developed by Nvidia. It is designed for datacenters and is parallel to Ada Lovelace. Named for computer scientist and United States Navy rear admiral Grace Hopper, the Hopper architecture was leaked in November 2019 and officially revealed in March 2022. It improves upon its predecessors, the Turing and Ampere microarchitectures, featuring a new streaming multiprocessor and a faster memory subsystem. The Nvidia Hopper H100 GPU is implemented using the TSMC 4N process with 80 billion transistors.
Processor designProcessor design is a subfield of computer science and computer engineering (fabrication) that deals with creating a processor, a key component of computer hardware. The design process involves choosing an instruction set and a certain execution paradigm (e.g. VLIW or RISC) and results in a microarchitecture, which might be described in e.g. VHDL or Verilog. For microprocessor design, this description is then manufactured employing some of the various semiconductor device fabrication processes, resulting in a die which is bonded onto a chip carrier.
Processor (computing)In computing and computer science, a processor or processing unit is an electrical component (digital circuit) that performs operations on an external data source, usually memory or some other data stream. It typically takes the form of a microprocessor, which can be implemented on a single metal–oxide–semiconductor integrated circuit chip. In the past, processors were constructed using multiple individual vacuum tubes, multiple individual transistors, or multiple integrated circuits. Today, processors use built-in transistors.
Digital signal processorA digital signal processor (DSP) is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing. DSPs are fabricated on MOS integrated circuit chips. They are widely used in audio signal processing, telecommunications, , radar, sonar and speech recognition systems, and in common consumer electronic devices such as mobile phones, disk drives and high-definition television (HDTV) products. The goal of a DSP is usually to measure, filter or compress continuous real-world analog signals.
Orthogonal matrixIn linear algebra, an orthogonal matrix, or orthonormal matrix, is a real square matrix whose columns and rows are orthonormal vectors. One way to express this is where QT is the transpose of Q and I is the identity matrix. This leads to the equivalent characterization: a matrix Q is orthogonal if its transpose is equal to its inverse: where Q−1 is the inverse of Q. An orthogonal matrix Q is necessarily invertible (with inverse Q−1 = QT), unitary (Q−1 = Q∗), where Q∗ is the Hermitian adjoint (conjugate transpose) of Q, and therefore normal (Q∗Q = QQ∗) over the real numbers.
Analytic function of a matrixIn mathematics, every analytic function can be used for defining a matrix function that maps square matrices with complex entries to square matrices of the same size. This is used for defining the exponential of a matrix, which is involved in the closed-form solution of systems of linear differential equations. There are several techniques for lifting a real function to a square matrix function such that interesting properties are maintained. All of the following techniques yield the same matrix function, but the domains on which the function is defined may differ.
CPU cacheA CPU cache is a hardware cache used by the central processing unit (CPU) of a computer to reduce the average cost (time or energy) to access data from the main memory. A cache is a smaller, faster memory, located closer to a processor core, which stores copies of the data from frequently used main memory locations. Most CPUs have a hierarchy of multiple cache levels (L1, L2, often L3, and rarely even L4), with different instruction-specific and data-specific caches at level 1.
Hardware-assisted virtualizationIn computing, hardware-assisted virtualization is a platform virtualization approach that enables efficient full virtualization using help from hardware capabilities, primarily from the host processors. A full virtualization is used to emulate a complete hardware environment, or virtual machine, in which an unmodified guest operating system (using the same instruction set as the host machine) effectively executes in complete isolation. Hardware-assisted virtualization was added to x86 processors (Intel VT-x, AMD-V or VIA VT) in 2005, 2006 and 2010 (respectively).
Massively parallel processor arrayA massively parallel processor array, also known as a multi purpose processor array (MPPA) is a type of integrated circuit which has a massively parallel array of hundreds or thousands of CPUs and RAM memories. These processors pass work to one another through a reconfigurable interconnect of channels. By harnessing a large number of processors working in parallel, an MPPA chip can accomplish more demanding tasks than conventional chips. MPPAs are based on a software parallel programming model for developing high-performance embedded system applications.
Computational complexityIn computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.
