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    <title>Inference on Tenu Tech Brief</title>
    <link>https://cluster-site.onrender.com/tags/inference/</link>
    <description>Recent content in Inference on Tenu Tech Brief</description>
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    <item>
      <title>DualPath: Breaking the Storage Bandwidth Bottleneck in Agentic LLM Inference</title>
      <link>https://cluster-site.onrender.com/posts/dualpath-breaking-the-storage-bandwidth-bottleneck-in-agentic-llm-inference/</link>
      <pubDate>Thu, 26 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/dualpath-breaking-the-storage-bandwidth-bottleneck-in-agentic-llm-inference/</guid>
      <description>• Computer Science &amp;gt; Distributed, Parallel, and Cluster Computing [Submitted on 25 Feb 2026] Title:DualPath: Breaking the Storage Bandwidth Bottleneck in Agentic LLM Inference View</description>
    </item>
    <item>
      <title>Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling</title>
      <link>https://cluster-site.onrender.com/posts/semantic-parallelism-redefining-efficient-moe-inference-via-model-data-co-scheduling/</link>
      <pubDate>Wed, 25 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/semantic-parallelism-redefining-efficient-moe-inference-via-model-data-co-scheduling/</guid>
      <description>• Computer Science &amp;gt; Machine Learning [Submitted on 6 Mar 2025 (v1), last revised 24 Feb 2026 (this version, v4)] Title:Semantic Parallelism: Redefining Efficient MoE Inference via</description>
    </item>
    <item>
      <title>Transform live video for mobile audiences with AWS Elemental Inference</title>
      <link>https://cluster-site.onrender.com/posts/transform-live-video-for-mobile-audiences-with-aws-elemental-inference/</link>
      <pubDate>Tue, 24 Feb 2026 18:55:11 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/transform-live-video-for-mobile-audiences-with-aws-elemental-inference/</guid>
      <description>• AWS News Blog Transform live video for mobile audiences with AWS Elemental Inference | Today, we&amp;rsquo;re announcing AWS Elemental Inference, a fully managed AI service that automatica</description>
    </item>
    <item>
      <title>A flaw in using pretrained protein language models in protein-protein interaction inference models</title>
      <link>https://cluster-site.onrender.com/posts/a-flaw-in-using-pretrained-protein-language-models-in-protein-protein-interaction-inference-models/</link>
      <pubDate>Tue, 24 Feb 2026 00:35:17 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/a-flaw-in-using-pretrained-protein-language-models-in-protein-protein-interaction-inference-models/</guid>
      <description>• Abstract With the growing pervasiveness of pretrained protein language models (pLMs), pLM-based methods are increasingly being put forward for the protein-protein interaction (PP</description>
    </item>
    <item>
      <title>CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models</title>
      <link>https://cluster-site.onrender.com/posts/codescaler-scaling-code-llm-training-and-test-time-inference-via-execution-free-reward-models/</link>
      <pubDate>Mon, 23 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/codescaler-scaling-code-llm-training-and-test-time-inference-via-execution-free-reward-models/</guid>
      <description>• Computer Science &amp;gt; Machine Learning [Submitted on 4 Feb 2026] Title:CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models View PDF HTML (</description>
    </item>
    <item>
      <title>Collaborative Processing for Multi-Tenant Inference on Memory-Constrained Edge TPUs</title>
      <link>https://cluster-site.onrender.com/posts/collaborative-processing-for-multi-tenant-inference-on-memory-constrained-edge-tpus/</link>
      <pubDate>Mon, 23 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/collaborative-processing-for-multi-tenant-inference-on-memory-constrained-edge-tpus/</guid>
      <description>• Computer Science &amp;gt; Distributed, Parallel, and Cluster Computing [Submitted on 19 Feb 2026] Title:Collaborative Processing for Multi-Tenant Inference on Memory-Constrained Edge TP</description>
    </item>
    <item>
      <title>Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge</title>
      <link>https://cluster-site.onrender.com/posts/ontology-guided-neuro-symbolic-inference-grounding-language-models-with-mathematical-domain-knowledge/</link>
      <pubDate>Mon, 23 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/ontology-guided-neuro-symbolic-inference-grounding-language-models-with-mathematical-domain-knowledge/</guid>
      <description>• Computer Science &amp;gt; Artificial Intelligence [Submitted on 19 Feb 2026] Title:Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge</description>
    </item>
    <item>
      <title>A flaw in using pretrained protein language models in protein-protein interaction inference models</title>
      <link>https://cluster-site.onrender.com/posts/a-flaw-in-using-pretrained-protein-language-models-in-protein-protein-interaction-inference-models/</link>
      <pubDate>Sun, 22 Feb 2026 00:35:29 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/a-flaw-in-using-pretrained-protein-language-models-in-protein-protein-interaction-inference-models/</guid>
      <description>• Abstract With the growing pervasiveness of pretrained protein language models (pLMs), pLM-based methods are increasingly being put forward for the protein-protein interaction (PP</description>
    </item>
    <item>
      <title>Accelerating Mobile Inference through Fine-Grained CPU-GPU Co-Execution</title>
      <link>https://cluster-site.onrender.com/posts/accelerating-mobile-inference-through-fine-grained-cpu-gpu-co-execution/</link>
      <pubDate>Fri, 20 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/accelerating-mobile-inference-through-fine-grained-cpu-gpu-co-execution/</guid>
      <description>• Computer Science &amp;gt; Machine Learning [Submitted on 24 Oct 2025 (v1), last revised 18 Feb 2026 (this version, v2)] Title:Accelerating Mobile Inference through Fine-Grained CPU-GPU</description>
    </item>
    <item>
      <title>Privacy-Aware Split Inference with Speculative Decoding for Large Language Models over Wide-Area Networks</title>
      <link>https://cluster-site.onrender.com/posts/privacy-aware-split-inference-with-speculative-decoding-for-large-language-models-over-wide-area-networks/</link>
      <pubDate>Fri, 20 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/privacy-aware-split-inference-with-speculative-decoding-for-large-language-models-over-wide-area-networks/</guid>
      <description>• Computer Science &amp;gt; Cryptography and Security [Submitted on 18 Feb 2026] Title:Privacy-Aware Split Inference with Speculative Decoding for Large Language Models over Wide-Area Net</description>
    </item>
    <item>
      <title>[RFC] TensaLang: A tensor-first language for LLM inference, lowering through MLIR to CPU/CUDA</title>
      <link>https://cluster-site.onrender.com/posts/rfc-tensalang-a-tensor-first-language-for-llm-inference-lowering-through-mlir-to-cpu/cuda/</link>
      <pubDate>Thu, 19 Feb 2026 22:24:46 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/rfc-tensalang-a-tensor-first-language-for-llm-inference-lowering-through-mlir-to-cpu/cuda/</guid>
      <description>• Hello, I&amp;rsquo;ve been working on a project called TensaLang and it&amp;rsquo;s finally at a point worth sharing. • It&amp;rsquo;s a small language + compiler + runtime for writing LLM forward passes dire</description>
    </item>
    <item>
      <title>DigitalOcean Gradient™ AI GPU Droplets Optimized for Inference: Increasing Throughput at Lower the Cost</title>
      <link>https://cluster-site.onrender.com/posts/digitalocean-gradient-ai-gpu-droplets-optimized-for-inference-increasing-throughput-at-lower-the-cost/</link>
      <pubDate>Thu, 19 Feb 2026 14:42:18 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/digitalocean-gradient-ai-gpu-droplets-optimized-for-inference-increasing-throughput-at-lower-the-cost/</guid>
      <description>• By Jason Peng and Hemasumanth Rasineni Production-grade LLM inference demands more than just access to GPUs; it requires deep optimization across the entire serving stack, from q</description>
    </item>
    <item>
      <title>Expanding our Agentic Inference Cloud: Introducing GPU Droplets Powered by AMD Instinct™ MI350X GPUs</title>
      <link>https://cluster-site.onrender.com/posts/expanding-our-agentic-inference-cloud-introducing-gpu-droplets-powered-by-amd-instinct-mi350x-gpus/</link>
      <pubDate>Thu, 19 Feb 2026 12:30:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/expanding-our-agentic-inference-cloud-introducing-gpu-droplets-powered-by-amd-instinct-mi350x-gpus/</guid>
      <description>• Expanding our Agentic Inference Cloud: Introducing GPU Droplets Powered by AMD Instinct™ MI350X GPUs ByWaverly Swinton Published:February 19, 2026 2 min read As our Agentic Infer</description>
    </item>
    <item>
      <title>Multi-agent cooperation through in-context co-player inference</title>
      <link>https://cluster-site.onrender.com/posts/multi-agent-cooperation-through-in-context-co-player-inference/</link>
      <pubDate>Thu, 19 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/multi-agent-cooperation-through-in-context-co-player-inference/</guid>
      <description>• Computer Science &amp;gt; Artificial Intelligence [Submitted on 18 Feb 2026] Title:Multi-agent cooperation through in-context co-player inference View PDF HTML (experimental)Abstract:Ac</description>
    </item>
    <item>
      <title>Multi-agent cooperation through in-context co-player inference</title>
      <link>https://cluster-site.onrender.com/posts/multi-agent-cooperation-through-in-context-co-player-inference/</link>
      <pubDate>Thu, 19 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/multi-agent-cooperation-through-in-context-co-player-inference/</guid>
      <description>• Computer Science &amp;gt; Artificial Intelligence [Submitted on 18 Feb 2026] Title:Multi-agent cooperation through in-context co-player inference View PDF HTML (experimental)Abstract:Ac</description>
    </item>
    <item>
      <title>Microsoft Rolls Out Next Inference Accelerator to Boost AI in Azure</title>
      <link>https://cluster-site.onrender.com/posts/microsoft-rolls-out-next-inference-accelerator-to-boost-ai-in-azure/</link>
      <pubDate>Thu, 19 Feb 2026 01:58:18 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/microsoft-rolls-out-next-inference-accelerator-to-boost-ai-in-azure/</guid>
      <description>• The company devised the new Maia 200 inference accelerator to improve cost and performance for AI inference processing in Azure Cloud Services.</description>
    </item>
    <item>
      <title>How NVIDIA Extreme Hardware-Software Co-Design Delivered a Large Inference Boost for Sarvam AI&#39;s Sovereign Models</title>
      <link>https://cluster-site.onrender.com/posts/how-nvidia-extreme-hardware-software-co-design-delivered-a-large-inference-boost-for-sarvam-ais-sovereign-models/</link>
      <pubDate>Wed, 18 Feb 2026 16:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/how-nvidia-extreme-hardware-software-co-design-delivered-a-large-inference-boost-for-sarvam-ais-sovereign-models/</guid>
      <description>• As global AI adoption accelerates, developers face a growing challenge: delivering large language model (LLM) performance that meets real-world latency and cost requirements. • R</description>
    </item>
    <item>
      <title>AST-PAC: AST-guided Membership Inference for Code</title>
      <link>https://cluster-site.onrender.com/posts/ast-pac-ast-guided-membership-inference-for-code/</link>
      <pubDate>Tue, 17 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/ast-pac-ast-guided-membership-inference-for-code/</guid>
      <description>• Computer Science &amp;gt; Artificial Intelligence [Submitted on 30 Jan 2026] Title:AST-PAC: AST-guided Membership Inference for Code View PDF HTML (experimental)Abstract:Code Large Lang</description>
    </item>
    <item>
      <title>AST-PAC: AST-guided Membership Inference for Code</title>
      <link>https://cluster-site.onrender.com/posts/ast-pac-ast-guided-membership-inference-for-code/</link>
      <pubDate>Tue, 17 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/ast-pac-ast-guided-membership-inference-for-code/</guid>
      <description>• Computer Science &amp;gt; Artificial Intelligence [Submitted on 30 Jan 2026] Title:AST-PAC: AST-guided Membership Inference for Code View PDF HTML (experimental)Abstract:Code Large Lang</description>
    </item>
    <item>
      <title>Announcing Amazon SageMaker Inference for custom Amazon Nova models</title>
      <link>https://cluster-site.onrender.com/posts/announcing-amazon-sagemaker-inference-for-custom-amazon-nova-models/</link>
      <pubDate>Mon, 16 Feb 2026 21:25:23 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/announcing-amazon-sagemaker-inference-for-custom-amazon-nova-models/</guid>
      <description>• AWS News Blog Announcing Amazon SageMaker Inference for custom Amazon Nova models | Since we launched Amazon Nova customization in Amazon SageMaker AI at AWS NY Summit 2025, cust</description>
    </item>
    <item>
      <title>How low-bit inference enables efficient AI</title>
      <link>https://cluster-site.onrender.com/posts/how-low-bit-inference-enables-efficient-ai/</link>
      <pubDate>Thu, 12 Feb 2026 18:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/how-low-bit-inference-enables-efficient-ai/</guid>
      <description>• In just the past few years, large machine learning models have made incredible strides. • Today&amp;rsquo;s models are not only remarkably capable but also achieve impressive results acros</description>
    </item>
    <item>
      <title>How low-bit inference enables efficient AI</title>
      <link>https://cluster-site.onrender.com/posts/how-low-bit-inference-enables-efficient-ai/</link>
      <pubDate>Thu, 12 Feb 2026 18:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/how-low-bit-inference-enables-efficient-ai/</guid>
      <description>• In just the past few years, large machine learning models have made incredible strides. • Today&amp;rsquo;s models are not only remarkably capable but also achieve impressive results acros</description>
    </item>
    <item>
      <title>The Container paradox: Why the Inference Cloud Demands a &#39;Decoupled&#39; Database</title>
      <link>https://cluster-site.onrender.com/posts/the-container-paradox-why-the-inference-cloud-demands-a-decoupled-database/</link>
      <pubDate>Tue, 10 Feb 2026 14:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/the-container-paradox-why-the-inference-cloud-demands-a-decoupled-database/</guid>
      <description>• The Container paradox: Why the Inference Cloud Demands a &amp;lsquo;Decoupled&amp;rsquo; Database ByKang Xie,Nicole Ghalwash,andZach Peirce Published:February 10, 2026 5 min read Kubernetes has won</description>
    </item>
    <item>
      <title>Parallel Track Transformers: Enabling Fast GPU Inference with Reduced Synchronization</title>
      <link>https://cluster-site.onrender.com/posts/parallel-track-transformers-enabling-fast-gpu-inference-with-reduced-synchronization/</link>
      <pubDate>Tue, 10 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/parallel-track-transformers-enabling-fast-gpu-inference-with-reduced-synchronization/</guid>
      <description>• Parallel Track Transformers: Enabling Fast GPU Inference with Reduced Synchronization Parallel Track Transformers: Enabling Fast GPU Inference with Reduced Synchronization Author</description>
    </item>
    <item>
      <title>Automating Inference Optimizations with NVIDIA TensorRT LLM AutoDeploy</title>
      <link>https://cluster-site.onrender.com/posts/automating-inference-optimizations-with-nvidia-tensorrt-llm-autodeploy/</link>
      <pubDate>Mon, 09 Feb 2026 18:30:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/automating-inference-optimizations-with-nvidia-tensorrt-llm-autodeploy/</guid>
      <description>• NVIDIA TensorRT LLM enables developers to build high-performance inference engines for large language models (LLMs), but deploying a new architecture traditionally requires signi</description>
    </item>
    <item>
      <title>Now Available: Anthropic Claude Opus 4.6 on DigitalOcean&#39;s Agentic Inference Cloud</title>
      <link>https://cluster-site.onrender.com/posts/now-available-anthropic-claude-opus-4.6-on-digitaloceans-agentic-inference-cloud/</link>
      <pubDate>Fri, 06 Feb 2026 19:38:29 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/now-available-anthropic-claude-opus-4.6-on-digitaloceans-agentic-inference-cloud/</guid>
      <description>• Now Available: Anthropic Claude Opus 4.6 on DigitalOcean&amp;rsquo;s Agentic Inference Cloud ByDigitalOcean Updated:February 6, 2026 2 min read Claude Opus 4.6 is now available on the Digi</description>
    </item>
    <item>
      <title>How we cut Vertex AI latency by 35% with GKE Inference Gateway</title>
      <link>https://cluster-site.onrender.com/posts/how-we-cut-vertex-ai-latency-by-35-with-gke-inference-gateway/</link>
      <pubDate>Fri, 06 Feb 2026 18:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/how-we-cut-vertex-ai-latency-by-35-with-gke-inference-gateway/</guid>
      <description>• How we cut Vertex AI latency by 35% with GKE Inference Gateway Product Manager Software Engineer Our most intelligent model is now available on Vertex AI and Gemini Enterprise As</description>
    </item>
    <item>
      <title>3 Ways NVFP4 Accelerates AI Training and Inference</title>
      <link>https://cluster-site.onrender.com/posts/3-ways-nvfp4-accelerates-ai-training-and-inference/</link>
      <pubDate>Fri, 06 Feb 2026 16:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/3-ways-nvfp4-accelerates-ai-training-and-inference/</guid>
      <description>• 3 Ways NVFP4 Accelerates AI Training and Inference L T F R E The latest AI models continue to grow in size and complexity, demanding increasing amounts of compute performance for</description>
    </item>
    <item>
      <title>LLM Inference Benchmarking - Measure What Matters</title>
      <link>https://cluster-site.onrender.com/posts/llm-inference-benchmarking-measure-what-matters/</link>
      <pubDate>Fri, 06 Feb 2026 14:46:06 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/llm-inference-benchmarking-measure-what-matters/</guid>
      <description>• By Piyush Srivastava, Karnik Modi, Stephen Varela, and Rithish Ramesh Production-grade LLM inference is a complex systems challenge, requiring deep co-designs - from hardware pri</description>
    </item>
    <item>
      <title>Maia 200: The AI accelerator built for inference</title>
      <link>https://cluster-site.onrender.com/posts/maia-200-the-ai-accelerator-built-for-inference/</link>
      <pubDate>Mon, 26 Jan 2026 16:00:30 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/maia-200-the-ai-accelerator-built-for-inference/</guid>
      <description>• Maia 200: 3nm TSMC accelerator with native FP8/FP4 tensor cores, 216GB HBM3e, 272MB SRAM. • Outperforms Amazon Trainium (3× FP4) and Google TPU v7 (FP8), delivering top‑tier infe</description>
    </item>
    <item>
      <title>Building the Inference Cloud, and What Comes Next</title>
      <link>https://cluster-site.onrender.com/posts/building-the-inference-cloud-and-what-comes-next/</link>
      <pubDate>Wed, 07 Jan 2026 17:29:20 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/building-the-inference-cloud-and-what-comes-next/</guid>
      <description>• Building the Inference Cloud, and What Comes Next ByPaddy Srinivasan CEO, DigitalOcean Published:January 7, 2026 4 min read 2025 was a defining year for DigitalOcean, not only be</description>
    </item>
    <item>
      <title>Token-count-based Batching: Faster, Cheaper Embedding Inference for Queries</title>
      <link>https://cluster-site.onrender.com/posts/token-count-based-batching-faster-cheaper-embedding-inference-for-queries/</link>
      <pubDate>Thu, 18 Dec 2025 15:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/token-count-based-batching-faster-cheaper-embedding-inference-for-queries/</guid>
      <description>• Token-count-based Batching: Faster, Cheaper Embedding Inference for Queries Embedding model inference often struggles with efficiency when serving large volumes of short requests</description>
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