gpu-architecture-advisor
Provide architecture-specific GPU optimization advice for NVIDIA GPUs (Ampere, Hopper, Ada). Use when discussing GPU architecture features, compute capability, or hardware-specific optimizations.
Browse published AI skills maintained by keith-mvs. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
28Repository stars across indexed skills
30Repository forks
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1Repository stars may repeat across skills from the same repository.
Provide architecture-specific GPU optimization advice for NVIDIA GPUs (Ampere, Hopper, Ada). Use when discussing GPU architecture features, compute capability, or hardware-specific optimizations.
Optimize CUDA kernels and GPU code for performance. Use when reviewing CUDA code, analyzing performance, or suggesting GPU optimizations.
Signal processing, filtering/denoising, and math-driven feature engineering.
Expert-level options trading framework for multi-leg strategy design, quantitative modeling, and programmatic execution using Alpaca Markets APIs. Covers straddles, butterflies, spreads, iron condors, and calen...
Advanced optimization for trading: OCO, multi-objective, DRO, MIP, Bayesian opt, plus convex/Markowitz/BL references.
. Use when . Requires .
Analyzes long straddle volatility plays with ATM call and put at same strike. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting large price movement in either direction...
Analyzes iron butterfly credit spreads with ATM short straddle and OTM long strangle protection. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting stock to pin at speci...
Probability, moments/tails, Bayes, and statistical learning foundations for systematic trading.
Assess credit risk and default probability for bonds using credit spreads, rating transitions, and recovery analysis. Requires numpy>=1.24.0, pandas>=2.0.0, scipy>=1.10.0. Use when evaluating corporate bonds, a...
Analyzes and implements married-put options strategies for portfolio protection. Calculates breakeven points, profit/loss scenarios, and compares strike prices (ITM, ATM, OTM) across multiple expiration cycles....
Implement covered call options strategy for income generation on long stock positions. Use when seeking to enhance returns through option premium collection while maintaining stock ownership. Covers structure,...
Monte Carlo, SDE simulation, Brownian/jump processes, discretization schemes.
Time series modeling, stationarity, ARIMA/GARCH, SDEs, and regime detection for trading.
Analyzes iron condor credit spreads with OTM put and call spreads for range-bound trading. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting sideways price action, want...
Compare bond performance against market benchmarks and indices. Analyzes yield spreads, duration matching, and relative value. Requires numpy>=1.24.0, pandas>=2.0.0. Use when evaluating bonds against peers, mea...
Factor modeling and portfolio construction (Markowitz, Black-Litterman, constraints, turnover).
Comprehensive financial statement analysis including ratio calculation, trend analysis, and peer comparison. Evaluates liquidity, profitability, efficiency, and leverage metrics. Requires numpy>=1.24.0, pandas>...
Price fixed income securities using present value, yield-to-maturity, and market conventions. Handles treasuries, corporates, municipals with various coupon frequencies. Requires numpy>=1.24.0, pandas>=2.0.0, s...
Tail risk, EVT, regularization, validation guardrails, and common pitfalls.
Analyzes long call butterfly spreads with 3 strikes and 4 legs for neutral outlook. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting minimal price movement, want low-c...
Analyzes bear-put-spread debit spreads for bearish directional plays with defined risk. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting moderate price decline, compar...
Game theory, network/systemic risk views, queueing/order-book, exchange notes.
Analyzes protective collar strategies combining long stock, long put protection, and short call income. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0. Use when protecting stock positions with reduced...
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