Search Results for "throughput" - Page 18

...It is trained from scratch and built using a hybrid architecture that integrates Transformer attention layers with Mamba-style sequence modeling components inside a Mixture-of-Experts framework. This architecture allows the system to maintain strong reasoning capabilities while improving throughput and reducing the computational cost associated with large context processing. The model is designed as a general-purpose language system capable of handling tasks such as chat interaction, coding assistance, document analysis, and instruction following.

NVIDIA-Nemotron-3-Super-120B-A12B-FP8 is a large-scale open language model developed by NVIDIA as part of the Nemotron-3 family of generative AI systems designed for advanced reasoning, conversational interaction, and agent-based workflows. The model contains approximately 120 billion parameters, but employs a Mixture-of-Experts architecture that activates only a smaller subset of parameters during inference, improving computational efficiency while maintaining high capability. Its...

Cost-efficient, High-Performance Open Source SMSC. PAiCore’s SMSC empowers SMS service providers with a high throughput, feature-rich messaging platform that boosts profit margins through full protocol interworking, including reliable HTTP and/or SMPP to SS7 conversion. Unlike closed-box solutions, our open source architecture offers flexible realtime SS7 parameter control via GUI or APIs, allowing customers to optimize delivery & costs. Built to handle over 100,000 TPS, our SMSC supports modern protocols such as SMPP, HTTP, SS7/SIGTRAN, Diameter for 4G/LTE, with others like SIP for IP-SM-GW capabilities and HTTP/2 for SMSF/5G capabilities soon to be added, making it a highly adaptable solution for current and future messaging demands.

Jupp is a Distributed Hash Table focusing on high throughput. It's main characteristics are: 1. Mechanisms for congestion control 2. O(log n) routing for arbitrary peer distributions in the ID space.

A Java-based mesoscopic, intermodal traffic simulator (MITS), providing a tool to evaluate scenarios (consisting of a road/rail/waterway network topology and load allocation) in terms of throughput, average speeds/travel times, congestion prediction.

...Unfortunately this implementation is no match for even one threaded SSE2 jpeg encoder, too much data goes through PCIe. Look at "Debunking the 100X GPU vs. CPU Myth: An Evaluation of Throughput Computing on CPU and GPU" paper by Victor W Lee, Changkyu Kim, Jatin Chhugani, Michael Deisher, Daehyun Kim, Anthony D. Nguyen, Nadathur Satish, Mikhail Smelyanskiy, Srinivas Chennupaty, Per Hammarlund, Ronak Singhal and Pradeep Dubey.

GigaChat 3 Ultra is a flagship instruct-model built on a custom Mixture-of-Experts architecture with 702B total and 36B active parameters. It leverages Multi-head Latent Attention to compress the KV cache into latent vectors, dramatically reducing memory demand and improving inference speed at scale. The model also employs Multi-Token Prediction, enabling multi-step token generation in a single pass for up to 40% faster output through speculative and parallel decoding techniques. Its...