aiDAPTIV TM

オンプレミスで実現する、プライベートかつ高速なLLM 推論と大規模学習

Technical Resources 

A benchmark only means something if you can see how it was made

Every published result identifies the workload, system, runtime, comparison, and limits.

What to show
Includes
Workload
Model, precision, prompt or dataset, task
System
CPU/GPU, unified-memory or discrete-memory architecture, operating system, cache memory configuration
Runtime
Version, quantization, relevant settings
Comparison
Baseline, metric, conditions, tradeoffs, limits
What to show

Workload

Includes

Model, precision, prompt or dataset, task

What to show

System

Includes

CPU/GPU, unified-memory or discrete-memory architecture, operating system, cache memory configuration

What to show

Runtime

Includes

Version, quantization, relevant settings

What to show

Comparison

Includes

Baseline, metric, conditions, tradeoffs, limits

Whitepapers and technical guides

Beyond VRAM and DRAM: Extending and Reusing KV Cache 

Learn how Pascari aiDAPTIV™ can extend eligible KV cache retention and reuse compatible shared input across document, RAG, coding, and agent workflows.

aiDAPTIV Middleware Resources

Access current aiDAPTIVLink 2 installation guidance, environment requirements, and fine-tuning workflow resources.

SEAMLESS INTEGRATION

  • Optimized middleware to extends GPU memory capacity
  • 2x 2TB aiDAPTIVCache to support 70B model
  • 低遅延

HIGH ENDURANCE

  • 業界をリードするDWPD 5 年以内に 1 日あたり 100 回の書き込み
  • 高度な NAND 修正アルゴリズムを備えた SLC NAND

aiDAPTIV+ BENEFITS

  • 簡単に実装
  • AI アプリケーションを変更する必要はありません
  • Reuse existing HW or add nodes

aiDAPTIV+ MIDDLEWARE

  • モデルを分割して各GPUに割り当てる
  • Hold pending slices on aiDAPTIVCache
  • Swap pending slices w/ finished slices on GPU

FOR SYSTEM INTEGRATORS

  • Access to ai100E SSD
  • Middleware library license

  • Full Phison support to bring up