Channels - MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces :: FRELIP Discovery

Similar Items: MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces

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CCL-Bench 1.0: A Trace-Based Benchmark for LLM Infrastructure
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Agentic Performance at the Edge: Insights from Benchmarking
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Back to the Future: Rethinking Endorsement in Order-Execute Blockchains
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VDCores: Resource Decoupled Programming and Execution for Asynchronous GPU
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From Barrier to Bridge: The Case for AI Data Center/Power Grid Co-Design
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Towards the Democratization and Standardization of Dynamic Resources with MPI Spawning
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Token Arena: A Continuous Benchmark Unifying Energy and Cognition in AI Inference
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Metal-Sci: A Scientific Compute Benchmark for Evolutionary LLM Kernel Search on Apple Silicon
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Cloud Performance Decomposition for Long-Term Performance Engineering: A Case Study
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ReCoVer: Resilient LLM Pre-Training System via Fault-Tolerant Collective and Versatile Workload
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On the Distortion of Partitioning Performance by Random Quantum Circuits
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FPGA-Accelerated Lock Management and Transaction Processing: Architecture, Optimization, and Design Space Exploration
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End-to-End and Phase-Level Performance Optimization for Hyperledger Fabric
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KEET: Explaining Performance of GPU Kernels Using LLM Agents
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FLAM: Evaluating Model Performance with Aggregatable Measures in Federated Learning
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Focus Session: Autonomous Systems Dependability in the era of AI: Design Challenges in Safety, Security, Reliability and Certification
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A Study on the Performance of Distributed Training of Data-driven CFD Simulations
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A Treasure Trove of Performance: Analyzing the IO500 Submission Data
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Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning
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Enhancing Performance Insight at Scale: A Heterogeneous Framework for Exascale Diagnostics
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Microbenchmark-Driven Analytical Performance Modeling Across Modern GPU Architectures
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Closer in the Gap: Towards Portable Performance on RISC-V Vector Processors
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Comparing the Performance of Heterogeneous Conjugate Gradient and Cholesky Solvers on Various Hardware Using SYCL
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Assessing Performance and Porting Strategies for Gravitational $N$-Body Simulations on the RISC-V-Based Tenstorrent Wormholetextsuperscript{texttrademark}