Programs written in C/C++ can suffer from serious memory fragmentation, leading to low utilization of memory, degraded performance, and application failure due to memory exhaustion.
Edd Barrett, Carl Friedrich Bolz-Tereick, Rebecca Killick +2
Virtual Machines (VMs) with Just-In-Time (JIT) compilers are traditionally thought to execute programs in two phases: the initial warmup phase determines which parts of a program would most benefit from dynamic compilation, before JIT compiling those parts into machine code; subsequently the program is said to be at a steady state of peak
The ability to record and replay program executions with low overhead enables many applications, such as reverse-execution debugging, debugging of hard-to-reproduce test failures, and "black box" forensic analysis of failures in deployed systems.
Deep learning's successes are often attributed to its ability to automatically discover new representations of the data, rather than relying on handcrafted features like other learning methods.
At initialization, artificial neural networks (ANNs) are equivalent to Gaussian processes in the infinite-width limit, thus connecting them to kernel methods.
MAC address randomization is a privacy technique whereby mobile devices rotate through random hardware addresses in order to prevent observers from singling out their traffic or physical location from other nearby devices.
Counting the number of ones in a binary stream is a common operation in database, information-retrieval, cryptographic and machine-learning applications.
Toke Høiland-Jørgensen, Michał Kazior, Dave Täht +2
With more devices connected, delays and jitter at the WiFi hop become more prevalent, and correct functioning during network congestion becomes more important.
We demonstrate a high-performance vendor-agnostic method for massively parallel solving of ensembles of ordinary differential equations (ODEs) and stochastic differential equations (SDEs) on GPUs.
The roots of Objective-C began at ITT in the early 1980s in a research group led by Tom Love investigating improving programmer productivity by an order of magnitude, a concern motivated by the perceived "software crisis" articulated in the late 1960s.
The fully connected layers of a deep convolutional neural network typically contain over 90% of the network parameters, and consume the majority of the memory required to store the network parameters.
Robert Buhren, Hans Niklas Jacob, Thilo Krachenfels +1
AMD Secure Encrypted Virtualization (SEV) offers protection mechanisms for virtual machines in untrusted environments through memory and register encryption.
Abstract Models of artificial intelligence (AI) that have billions of parameters can achieve high accuracy across a range of tasks 1,2 , but they exacerbate the poor energy efficiency of conventional general-purpose processors, such as graphics processing units or central processing units.