ROCm/aiter
Dec 2025 – Jan 2026
2 Months active
Languages Used
COPython
Technical Skills
GPU ProgrammingKernel DevelopmentPerformance OptimizationAPI DevelopmentDeep LearningMachine Learning
Sergey Solovyev
PROFILE
Sergey Solovyev
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
279
Activity Months2
Your Network
1526 people
Work History
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026: Delivered a dynamic paged attention API switching between ASM and HIP to optimize kernel selection based on workload characteristics. Implemented integration through paged_attention_common with shuffled KV cache layout considerations and quantization support, plus code quality and formatting improvements to bolster maintainability. HIP demonstrated better performance for low-concurrency workloads (<128), contributing to improved inference throughput in typical low-traffic scenarios. Updated unit tests and cleaned up test scaffolding, removing outdated tests and redundant parameters to reduce maintenance burden.
1 Commits • 1 Features
Jan 1, 2026January 2026: Delivered a dynamic paged attention API switching between ASM and HIP to optimize kernel selection based on workload characteristics. Implemented integration through paged_attention_common with shuffled KV cache layout considerations and quantization support, plus code quality and formatting improvements to bolster maintainability. HIP demonstrated better performance for low-concurrency workloads (<128), contributing to improved inference throughput in typical low-traffic scenarios. Updated unit tests and cleaned up test scaffolding, removing outdated tests and redundant parameters to reduce maintenance burden.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 20252025-12 monthly performance summary for ROCm/aiter: delivered a kernel tiling optimization for large-token inputs (32x384 tiling) and introduced a 32x384 blockscale FP8 FMoE kernel. Validated on Qwen3 235B with CONC=256, showing a 2.5% uplift in the larger case and an expected ~20% uplift vs 32x256 tiling for large-token inputs. No critical bugs reported; the work lays groundwork for improved throughput and scalability on large LLMs.
December 2025
1 Commits • 1 Features
Dec 1, 20252025-12 monthly performance summary for ROCm/aiter: delivered a kernel tiling optimization for large-token inputs (32x384 tiling) and introduced a 32x384 blockscale FP8 FMoE kernel. Validated on Qwen3 235B with CONC=256, showing a 2.5% uplift in the larger case and an expected ~20% uplift vs 32x256 tiling for large-token inputs. No critical bugs reported; the work lays groundwork for improved throughput and scalability on large LLMs.
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
COPython
Technical Skills
API DevelopmentDeep LearningGPU ProgrammingKernel DevelopmentMachine LearningPerformance OptimizationPyTorch
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