Search Results for "high performance computing"

...The fundamental idea is: sample a task, train on that task (inner loop), and then move the initialization parameters toward the adapted parameters (outer loop). Because Reptile is a first-order algorithm, it avoids computing second derivatives or full meta-gradients, making it computationally simpler while retaining good performance. The repo includes training scripts, dataset fetchers (Omniglot, Mini-ImageNet), and modules for defining the Reptile update logic, variables, and hyperparameters.

...The core idea is to build an automaton from a dictionary of patterns, then stream through input text to emit matches with minimal overhead. By using a double-array trie representation, the project emphasizes performance and memory efficiency compared to simpler pointer-heavy trie structures, which can matter a lot for large dictionaries or latency-sensitive services. This makes it a strong fit for tasks like content filtering, entity/term spotting, dictionary-based annotation, or high-throughput log/text processing. In short, it’s a specialized, speed-focused library for industrial-strength multi-keyword matching in Java.

TommyDS is a C library of hashtables and tries designed for high performance.

parFE is fully-parallel high-performance finite element code targeted to the modeling of trabecular bones in humans. It employs scalable multigrid solvers for efficient solutions on massively parallel computers.

Fast cython implementation of trie data structure for Python. Development is inactive, but moved to: http://github.com/martinkozak/cytrie.

A collection of Concurrent and Highly Scalable Utilities. These are intended as direct replacements for the java.util.* or java.util.concurrent.* collections but with better performance when many CPUs are using the collection concurrently.

SSEPlus is a SIMD function library. It provides optimized emulation for newer SSE instructions. It also provides a rich set of high performance routines for common operations such as arithmetic, bitwise logic, and data packing and unpacking.

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.

High-performance computing code and libraries used in the High Performance Computing subject in Telecommunications Engineering at the University of Granada (http://geneura.ugr.es/~jmerelo/asignaturas/AAP)