--- title: "Computing & GPUs — papers" description: "Computing & GPUs: 121 papers of the Elamur Research library · page 1 of 5 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/computing/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/computing/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / Computing & GPUs # 🖥️ Computing & GPUs 121 papers · page 1 of 5 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) GPUs and parallel computing, compilers and languages, systems, databases, security, search and the web. **1** [2](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) … [5](https://md.research.elamur.ai/free/en/shelves/computing/page/5/) [next →](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) - [AlphaEvolve: A coding agent for scientific and algorithmic discovery](https://md.research.elamur.ai/free/en/papers/novikov-2025-alphaevolve-coding-agent-scientific-algorithmic/) — Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al. · 2025 - [KernelBench: Can LLMs Write Efficient GPU Kernels?](https://md.research.elamur.ai/free/en/papers/ouyang-2025-kernelbench-llms-write-efficient-gpu/) — Anne Ouyang, Simon Guo, Simran Arora, et al. · 2025 - [Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/) — Jingyang Yuan, Huazuo Gao, Damai Dai, et al. · 2025 - [Break the Sequential Dependency of LLM Inference Using Lookahead Decoding](https://md.research.elamur.ai/free/en/papers/fu-2024-break-sequential-dependency-llm-inference/) — Yichao Fu, Peter Bailis, Ion Stoica, et al. · 2024 - [Code Llama: Open Foundation Models for Code](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/) — Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al. · 2024 - [CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/) — Alex Gu, Baptiste Rozière, Hugh Leather, et al. · 2024 - [DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) — Jeffrey Li, Alex Fang, Georgios Smyrnis, et al. · 2024 - [DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads](https://md.research.elamur.ai/free/en/papers/xiao-2024-duoattention-efficient-long-context-llm/) — Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al. · 2024 - [EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/) — Yuhui Li, Fangyun Wei, Chao Zhang, et al. · 2024 - [KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache](https://md.research.elamur.ai/free/en/papers/liu-2024-kivi-tuning-free-asymmetric-2bit/) — Zirui Liu, Jiayi Yuan, Hongye Jin, et al. · 2024 - [KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization](https://md.research.elamur.ai/free/en/papers/hooper-2024-kvquant-towards-10-million-context/) — Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, et al. · 2024 - [LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/) — Naman Jain, King Han, Alex Gu, et al. · 2024 - [LLM in a flash: Efficient Large Language Model Inference with Limited Memory](https://md.research.elamur.ai/free/en/papers/alizadeh-2024-llm-flash-efficient-large-language/) — Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al. · 2024 - [Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads](https://md.research.elamur.ai/free/en/papers/cai-2024-medusa-simple-llm-inference-acceleration/) — Tianle Cai, Yuhong Li, Zhengyang Geng, et al. · 2024 - [QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/) — Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al. · 2024 - [QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks](https://md.research.elamur.ai/free/en/papers/tseng-2024-quip-even-better-llm-quantization/) — Albert Tseng, Jerry Chee, Qingyao Sun, et al. · 2024 - [SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://md.research.elamur.ai/free/en/papers/yang-2024-swe-agent-agent-computer-interfaces/) — John Yang, Carlos E. Jimenez, Alexander Wettig, et al. · 2024 - [SWE-bench: Can Language Models Resolve Real-World GitHub Issues?](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/) — Carlos E. Jimenez, John Yang, Alexander Wettig, et al. · 2024 - [The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale](https://md.research.elamur.ai/free/en/papers/penedo-2024-fineweb-datasets-decanting-web-finest/) — Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al. · 2024 - [WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/) — Seungju Han, Kavel Rao, Allyson Ettinger, et al. · 2024 - [XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/) — Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al. · 2024 - [An Open Dataset and Model for Language Identification](https://md.research.elamur.ai/free/en/papers/burchell-2023-open-dataset-model-language-identification/) — Laurie Burchell, Alexandra Birch, Nikolay Bogoychev, et al. · 2023 - [DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models](https://md.research.elamur.ai/free/en/papers/jacobs-2023-deepspeed-ulysses-system-optimizations-enabling/) — Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, et al. · 2023 - [FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU](https://md.research.elamur.ai/free/en/papers/sheng-2023-flexgen-high-throughput-generative-inference/) — Ying Sheng, Lianmin Zheng, Binhang Yuan, et al. · 2023 - [From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference](https://md.research.elamur.ai/free/en/papers/samsi-2023-words-watts-benchmarking-energy-costs/) — Siddharth Samsi, Dan Zhao, Joseph McDonald, et al. · 2023 **1** [2](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) … [5](https://md.research.elamur.ai/free/en/shelves/computing/page/5/) [next →](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) - [← previous shelf Aramaic](https://md.research.elamur.ai/free/en/shelves/arc/) - [next shelf → Economics & trade](https://md.research.elamur.ai/free/en/shelves/economics/) - [↑ back to shelves](https://md.research.elamur.ai/free/en/shelves/)