Dr. Alex J. Rivera¹, Prof. Mei‑Lin Chen², Eng. Omar H. Patel³
While the above studies provide valuable context, has yet been published. Our work thus extends the literature by delivering a full‑stack evaluation that bridges hardware, firmware, and system‑level performance. 3. Experimental Methodology 3.1 Testbed Configuration | Component | Specification | |-----------|----------------| | Chassis | Dell PowerEdge MIDV945RM, 24‑U, 2‑rail (front/rear) airflow. | | CPUs | 4 × Intel Xeon ® Scalable ® (4th Gen “Sapphire Rapids”) – 56 cores each, 3.2 GHz base, 5.0 GHz turbo, TDP = 300 W. | | Memory | 8 × 32 GB DDR5‑5600 ECC RDIMM (total 256 GB). | | Accelerators | 4 × NVIDIA RTX A6000 (PCIe 5.0, 48 GB VRAM) for AI‑training runs. | | Storage | 8 × 2 TB Intel Optane SSD PM (NVMe 2.0, 7 GB/s read). | | Network | 2 × Mellanox ConnectX‑7 (200 GbE, RoCEv2). | | Power | Dual 2400 W hot‑swap PSUs (80 PLUS Platinum). | | Management | iDRAC9 Enterprise, OpenManage Enterprise (OME) 4.5, Redfish API v1.6. | | OS | Ubuntu 24.04 LTS (kernel 6.8) with Linux‑kernel‑4.19 fallback for baseline comparison. | | Hypervisor | VMware ESXi 8.0u3 (for VDI workloads). | | Benchmark Suite | SPEC‑CPU2017 (int_rate, fp_rate), MLPerf Training v2.0 (ResNet‑50, BERT‑Large), VDI‑Scale (PCoIP 16‑user), Ceph RADOS Bench (4 KB random read/write). | | Power Measurement | Yokogawa WT310 Power Analyzer, sampling at 1 kHz, data logged via IPMI. | | Thermal Sensors | On‑board DTS (Digital Thermal Sensors), external Fluke Ti300 thermal camera for hotspot verification. | midv945rm
Key CPU features:
¹ Department of Computer Engineering, University of Southern California, Los Angeles, CA, USA ² Institute of Advanced Computing, Tsinghua University, Beijing, China ³ Dell Technologies – Advanced Systems Group, Austin, TX, USA Mei‑Lin Chen², Eng