Add initial KV Cache benchmark implementation for MLPerf Storage v3

kv_cache_benchmark/README.md

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+# MLPerf Storage KV Cache Benchmark
+
+This directory contains the initial implementation of the KV Cache benchmark for MLPerf Storage v3.
+
+## Overview
+
+The KV Cache benchmark simulates the storage access patterns of Large Language Model (LLM) inference systems, specifically focusing on key-value cache operations that are critical for multi-turn conversations and long-context processing.
+
+## Components
+
+### Core Scripts
+
+- **kv-cache.py**: Main benchmark implementation for KV cache storage performance testing
+- **kv-cache_sharegpt_replay.py**: ShareGPT conversation replay-based benchmark for realistic workload simulation
+- **kv-cache-wrapper.sh**: Wrapper script for running benchmark configurations
+- **validate.sh**: Validation script for benchmark results
+
+### Documentation
+
+- **MLperf v3 KV cache proposal.md**: Detailed proposal for KV cache benchmark integration into MLPerf Storage
+- **MLperf v3 KV cache proposal.pdf**: PDF version of the proposal
+- **sources.md**: References and source documentation
+
+## Purpose
+
+This benchmark addresses the growing need to measure storage system performance under AI/ML inference workloads, particularly:
+
+- Key-value cache read/write patterns
+- Mixed sequential and random access patterns
+- Multi-threaded concurrent access
+- Realistic conversation-based workload replay
+
+## Getting Started
+
+See the proposal documents for detailed information about the benchmark design, metrics, and validation criteria.
+
+## Status
+
+Initial implementation - work in progress for MLPerf Storage v3.0