Search Results for "throughput"
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13 projects for "throughput" with 2 filters applied:
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1
Napkin Math
Techniques and numbers for estimating system's performance
...It collects practical numbers, benchmark-style measurements, and mental models that help engineers make fast back-of-the-envelope calculations. The project is useful for questions like how much memory throughput matters, how long storage operations may take, what network latency to expect, or how expensive logging could become at high request volume. It treats these values as rounded numbers for reasoning rather than exact performance guarantees. The repository is especially useful for system design interviews, architecture planning, capacity estimation, and infrastructure cost discussions. ... -
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CoreNet
CoreNet: A library for training deep neural networks
...CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. CoreNet integrates tightly with Apple’s proprietary ML stack and hardware, serving as the foundation for research in computer vision, language models, and multimodal systems within Apple AI. The framework includes monitoring tools, fault tolerance mechanisms, and efficient checkpointing for massive training runs. -
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DeepEP
DeepEP: an efficient expert-parallel communication library
DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP addresses that by providing optimized GPU kernels and efficient dispatch/combining logic. ... -
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FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to efficiently manage memory during decoding. On very compute-bound settings, it can reach up to ~660 TFLOPS on H800 SXM5 hardware, while in memory-bound configurations it can push memory throughput to ~3000 GB/s. ... -
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Node RDKafka
Node.js bindings for librdkafka
A high-performance Node.js client for Apache Kafka, built on top of librdkafka, providing bindings for efficient Kafka message processing. -
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frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
...Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run multiple predictions in parallel, thus utilizing as many CPUs as you like to improve the overall prediction throughput of your application/pipeline. -
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workerpool
Offload tasks to a pool of workers on node.js and in the browser
...It supports task queuing, dynamic worker scaling, timeouts, transferable objects, and proxy-based APIs for interacting with worker functions as if they were local calls. workerpool is designed to improve application responsiveness and throughput in workloads involving heavy computation, data processing, or asynchronous execution. The library works across multiple environments, supporting Web Workers in browsers and Worker Threads or child processes in Node.js. Its architecture emphasizes ease of integration, scalability, and efficient concurrency management for modern JavaScript applications. -
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TensorStore
Library for reading and writing large multi-dimensional arrays
...Transactional semantics allow atomic updates and consistent snapshots, which is essential for large, shared datasets used by ML and scientific workflows. The library is engineered for scalability—background caching, chunk sharding, and retryable operations keep throughput high even over unreliable networks. With language bindings, it fits into Python-heavy analysis pipelines while retaining a fast C++ core. -
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Honggfuzz
Security oriented software fuzzer
honggfuzz is a general-purpose, high-performance fuzzer that mixes coverage feedback with practical crash triage to uncover memory-safety and logic bugs. It supports multiple fuzzing modes—stdin, file, and networking—so targets can be exercised the same way they run in production. Instrumentation via compiler hooks or hardware/perf counters guides mutations toward previously unseen edges, while persistent mode keeps the target process alive to amortize startup costs. The tool integrates... -
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HighwayHash
Fast strong hash functions: SipHash/HighwayHash
...It’s designed to defeat hash-flooding attacks by mixing input with wide SIMD operations and a branch-free inner loop, so adversaries can’t cheaply craft many colliding keys. The implementation targets multiple CPU families with vectorized code paths while keeping a portable fallback, yielding high throughput across platforms. It exposes simple one-shot and streaming APIs, so you can hash short keys or long byte streams with the same function. Typical uses include protecting hash tables that store untrusted keys and authenticating short-lived messages or records in storage systems. Although not a replacement for collision-resistant digests like SHA-2/3, it strikes a pragmatic balance of speed, simplicity, and resistance to common abuse patterns seen in production backends. -
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PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
PerfKitBenchmarker is an open-source benchmarking framework designed to measure and compare the performance of cloud infrastructure across multiple providers in a consistent and reproducible way. It allows users to evaluate metrics such as latency, throughput, provisioning time, and system performance using a standardized set of benchmarks. The tool supports a wide range of environments, including major cloud platforms, Kubernetes clusters, and even local hardware, making it highly versatile for performance analysis. It simplifies the process of running complex benchmarks by providing unified command-line workflows that handle resource provisioning, execution, and result collection. ... -
12
Erlang Resource Pool
Resource Pool manages reusable resources among multiple processes.
...The goal of the tool is reduce the overhead of creating new resources by reusing of the same resources among multiple processes. Achieving result is better performance and throughput. The resource pool was inspired by Java Apache's commons pool and adopts API and main principals from this project. Database connection is most popular example for pooling resource. -
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rmisockfactory
Collection of RMI Socket Factories
This project contains a collection of RMI socket factories -- for instance gzip-encoded data sent over the wire, NIO-based communication etc.
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