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Internal CPU Accelerators and HBM Enable Faster and Smarter HPC and AI Applications

  • RobFarber 
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Internal CPU Accelerators and HBM Enable Faster and Smarter HPC and AI Applications

We have now entered the era when processor designers can leverage modular semiconductor manufacturing capabilities to speed frequently performed operations (such as small tensor operations) and offload a variety of housekeeping tasks (such as copying and zeroing memory) to dedicated on-chip accelerators. The idea is to have software make the hardware work smarter. CPU designers can also incorporate high-bandwidth memory (HBM) modules to dramatically increase the amount of data per second that can be supplied to these accelerated processor cores. This means that these modular processors can work both faster and smarter as more of the accelerated cores can be kept busy processing data.

The technology Intel is delivering in the accelerator engines used in 4th Gen Intel® Xeon® processors reflects a phase transition as they are now delivering a choice of accelerator technology to customers. With the introduction of the HBM-enabled Intel® Xeon® CPU Max Series processors, Intel is now uniquely positioned to demonstrate the benefits of accelerated processor cores across a wide variety of AI and HPC data-intensive workloads. The benchmark results are compelling.[1]

HPC and AI users will be particularly interested in the accelerated capabilities of the Intel® Advanced Matrix Extensions (Intel® AMX) and the Intel® Data Streaming Accelerator (Intel® DSA).

  • Intel DSA: Intel benchmarks for the DSA vary according to workload and operation performed. Speedups include faster AI training by having the DSA zero memory in the kernel, increased IOP/s/core by offloading CRC generation during storage operations, and of course, MPI speedups that include higher throughput for shmem data copies.  For example, Intel quotes a 1.7× increase in IOP/s rate for large sequential packet reads when using DSA compared to using the Intel® Intelligent Storage Acceleration Library without DSA.[2]
  • Intel AMX: Intel AMX delivers 3× to 10× higher inference and training performance versus the previous generation on AI workloads that use bint8 and bfloat16 matrix operations. [3] [4]

HPC architects and cloud users will also be interested in the performance per watt gains provided by these on-chip accelerators.

Modern Modular Semiconductor Architecture Design Requires an Ecosystem

Intel AMX, Intel DSA, and on-chip HBM reflect the power of a design methodology that uses modular semiconductor building blocks (Figure 1). Chip modularity cannot be added in isolation. Along with the necessary manufacturing capability, this modularity also requires a scalability on-chip communications fabric such as the Intel Xeon Scalable processor mesh fabric.

Internal CPU Accelerators and HBM Enable Faster and Smarter HPC and AI Applications
Figure 1. The power of a modular design is shown in the Intel Xeon Max CPU. (Information about other acceleration engines such as Intel® Dynamic Load Balancer (Intel® DLB) , Intel® In-Memory Analytics Accelerator (Intel® IAA) , and Intel® QuickAssist Technology (Intel® QAT) can be found in the Intel Accelerator Engines Fact Sheet.) Purple tabs represent tehnologies that exist in both 4th Gen Intel Xeon processors and Intel Xeon Max processors.

Transitioning to modular hardware design also requires that the supporting software ecosystem transparently enable the use of the features of the modules and accelerators. Otherwise, software developers will become overwhelmed with having to support the combinatorics of all possible on-chip modules and accelerators.

Matching software capability to hardware modularity explains why Intel (a semiconductor manufacturing company) has invested extensively in oneAPI and an open ecosystem of libraries and standards-based software components. The Intel AMX extensions are transparently accessible from popular libraries and applications including TensorFlow and PyTorch. Intel DSA engine can be accessed via the IDXD kernel driver or Data Plane Development Kit (DPDK) supported drivers. Recent Linux kernels already support DSA for operations such as zeroing memory. The open-source libfabric library also uses the Intel DSA accelerator as does Intel® MPI.[5]

DSA

Intel DSA is a high-performance data copy that is also, importantly, a data transformation accelerator. It is designed to optimize streaming data movement and transformation operations that are common in high-performance storage, networking, persistent memory, and various data processing applications.

The goal of the accelerator is to provide higher overall system performance for workloads that involve lots of data movement and transformation operations by freeing CPU cycles to perform higher-level functions (Figure 2). The ability to perform data transformation operations makes the Intel DSA accelerator a far more capable accelerator than a simple DMA offload engine. Common Intel DSA operations include zeroing memory; generating and testing CRC checksums; and performing Data Integrity Field (DIF) calculations to support storage and networking applications — all at very high speed.

Internal CPU Accelerators and HBM Enable Faster and Smarter HPC and AI Applications
Figure 2. DSA performance metrics[6]

AMX

GPUs are well-known for accelerating small matrix operations and providing reduced precision arithmetic to speed up some AI workloads. Popular machine learning applications such as TensorFlow and PyTorch make it easy to use these capabilities on a GPU.

Intel introduced Intel AMX as a built-in accelerator to improve the performance of deep-learning training and inference on the CPU. Just as with a GPU, these Intel AMX capabilities can be accessed from popular AI libraries and applications.

Lisa Spelman, Intel corporate vice president and general manager of Intel Xeon products, highlighted the benefits in a recent March 2023 investor webinar by noting that in a head-to-head competition between a 48-core 4th Gen Intel Xeon and a 48-core 4th Gen AMD Epyc CPU, the 4th Gen Xeon delivered an average performance gain of 4 times the competition’s performance on a broad set of deep-learning workloads.[7] (See Figure 4 below for additional performance per watt benchmark results and other results reported on the web.)

Power Efficiency

Along with increased application performance, accelerators can also deliver dramatic power benefits. Maximizing performance for every watt of power utilized is a major concern at HPC and cloud data centers around the world. Comparing the relative performance per watt on a 4th gen Intel Xeon processor running accelerated vs. non-accelerated software shows a significant performance per watt benefit — especially for Intel AMX accelerated workloads.

Internal CPU Accelerators and HBM Enable Faster and Smarter HPC and AI Applications
Figure 3. Accelerator performance per watt benchmarks[8].

HBM

HBM is a gateway technology to faster time-to-solution with real-world benefits. While the promise of peak performance may entice many with trillions of operations per second (TFlop/s), the reality is that actual performance for most applications ultimately depends on the memory subsystem. According to the HBM2e specification, a single stack can deliver up to 307 GB/s, but some manufacturers already exceed this.[9] The new Intel Xeon Max processors can realize more than 16 GB/s of HBM memory capacity per core without having to drop the core count. This can equate to significantly faster time to solve on many workloads (Figure 4).

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Figure 4. Real-world Intel Xeon Max CPU performance reported by Intel.[10]

Memory is key to performance, which is why both the HBM and DDR5 memory controllers are tightly integrated inside the chip so they can work directly with HBM and DDR5 with high efficiency. This leverages the mesh architecture used by the Intel Xeon processors. Basically, each core and last-level cache (LLC) slice has a combined Caching and Home Agent (CHA), which provides scalability of resources across the mesh for Intel® Ultra Path Interconnect (Intel® UPI) cache coherency functionality without any hotspots (Figure 1). This means that each computes and HBM tile is a NUMA domain with associated local memory, which gives applications the ability to minimize the data movement across the chip and therefore increase performance.

Conclusion

Products based on modular semiconductor design and manufacturing are now entering the market. This means we can now evaluate accelerated processor designs that can speed frequently performed operations (such as small tensor operations) and offload a variety of housekeeping tasks like zeroing memory and performing CRC calculations. Even better, we can now also evaluate the benefits of faster HBM on data-intensive workloads along with the power and performance benefits accrued when these accelerated cores are provided with more data per unit of time. Thus far, the results are extremely encouraging.

Rob Farber is a technology consultant and author with an extensive background in HPC and machine learning technology.

[1] See also Getting More Out of Every High Performance Computing Core

[2] See [N18] at http://intel.com/processorclaims : 4th Gen Intel® Xeon® Scalable processors. Results may vary.

[3] https://www.nextplatform.com/2023/01/16/application-acceleration-for-the-masses/

[4] https://www.intel.com/content/www/us/en/newsroom/news/4th-gen-xeon-scalable-processors-max-series-cpus-gpus.html

[5] https://cdrdv2-public.intel.com/759709/353216-data-streaming-accelerator-user-guide-2.pdf

[6] https://dsatutorial.web.illinois.edu/

[7] See [N18] at http://intel.com/processorclaims: 4th Gen Intel® Xeon® Scalable processors. Results may vary.

[8]See slide 8 in https://www.colfax-intl.com/downloads/Public-Accelerators-Deep-Dive-Presentation-Intel-DSA.pdf

[9] https://en.wikipedia.org/wiki/High_Bandwidth_Memory

[10] LAMMPS (Atomic Fluid, Copper, DPD, Liquid_crystal, Polyethylene, Protein, Stillinger-Weber, Tersoff, Water)

Intel® Xeon® 8380: Test by Intel as of 10/11/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, NUMA configuration SNC2, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, LAMMPS v2021-09-29 cmkl:2022.1.0, icc:2021.6.0, impi:2021.6.0, tbb:2021.6.0; threads/core:; Turbo:on; BuildKnobs:-O3 -ip -xCORE-AVX512 -g -debug inline-debug-info -qopt-zmm-usage=high;

Intel® Xeon® 8480+: Test by Intel as of 9/29/2022. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, SNC4, Total Memory 512 GB (16x32GB 4800MT/s, DDR5), BIOS Version SE5C7411.86B.8713.D03.2209091345, ucode revision=0x2b000070, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, LAMMPS v2021-09-29 cmkl:2022.1.0, icc:2021.6.0, impi:2021.6.0, tbb:2021.6.0; threads/core:; Turbo:off; BuildKnobs:-O3 -ip -xCORE-AVX512 -g -debug inline-debug-info -qopt-zmm-usage=high;

Intel® Xeon® Max 9480: Test by Intel as of 9/29/2022. 1-node, 2x Intel® Xeon® Max 9480, HT ON, Turbo ON, NUMA configuration SNC4, Total Memory 128 GB (HBM2e at 3200 MHz), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, LAMMPS v2021-09-29 cmkl:2022.1.0, icc:2021.6.0, impi:2021.6.0, tbb:2021.6.0; threads/core:; Turbo:off; BuildKnobs:-O3 -ip -xCORE-AVX512 -g -debug inline-debug-info -qopt-zmm-usage=high;

DeePMD (Multi-Instance Training)

Intel® Xeon® 8380: Test by Intel as of 10/20/2022. 1-node, 2x Intel® Xeon® 8380 processor, Total Memory 256 GB, kernel 4.18.0-372.26.1.eI8_6.crt1.x86_64, compiler gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-10), https://github.com/deepmodeling/deepmd-kit, Tensorflow 2.9, Horovod 0.24.0, oneCCL-2021.5.2, Python 3.9

3.9

Intel® Xeon® 8480+: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® 8480+, Total Memory 512 GB, kernel 4.18.0-365.eI8_3x86_64, compiler gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-10), https://github.com/deepmodeling/deepmd-kit, Tensorflow 2.9, Horovod 0.24.0, oneCCL-2021.5.2, Python 3.9

Intel® Xeon® Max 9480: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® Max 9480, Total Memory 128 GB (HBM2e at 3200 MHz), kernel 5.19.0-rc6.0712.intel_next.1.x86_64+server, compiler gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-13), https://github.com/deepmodeling/deepmd-kit, Tensorflow 2.9, Horovod 0.24.0, oneCCL-2021.5.2, Python 3.9

Quantum Espresso (AUSURF112, Water_EXX)

Intel® Xeon® 8380: Test by Intel as of 9/30/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, Quantum Espresso 7.0, AUSURF112, Water_EXX

Intel® Xeon® 8480+: Test by Intel as of 9/2/2022. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, Total Memory 512 GB (16x32GB 4800MT/s, Dual-Rank), ucode revision= 0x90000c0, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, Quantum Espresso 7.0, AUSURF112, Water_EXX

Intel® Xeon® Max 9480: Test by Intel as of 9/2/2022. 1-node, 2x   Intel® Xeon® Max 9480, HT On, Turbo On, SNC4, Total Memory 128 GB (8x16GB HBM2 3200MT/s), ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, Quantum Espresso 7.0, AUSURF112, Water_EXX

ParSeNet (SplineNet)

Intel® Xeon® 8380: Test by Intel as of 10/18/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C6200.86B.0020.P23.2103261309, ucode revision=0xd000270, Rocky Linux 8.6, Linux version 4.18.0-372.19.1.el8_6.crt1.x86_64, ParSeNet (SplineNet), PyTorch 1.11.0, Torch-CCL 1.2.0, IPEX 1.10.0, MKL (20220804), oneDNN (v2.6.0)

Intel® Xeon® 8480+: Test by Intel as of 10/18/2022. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, Total Memory 512 GB (16x32GB 4800MT/s, Dual-Rank), BIOS Version EGSDCRB1.86B.0083.D22.2206290535, ucode revision=0xaa0000a0, CentOS Stream 8, Linux version 4.18.0-365.el8.x86_64, ParSeNet (SplineNet), PyTorch 1.11.0, Torch-CCL 1.2.0, IPEX 1.10.0, MKL (20220804), oneDNN (v2.6.0)

Intel® Xeon® Max 9480: Test by Intel as of 09/12/2022. 1-node, 2x Intel® Xeon® Max 9480, HT On, Turbo On, SNC4, Total Memory 128 GB (8x16GB HBM2 3200MT/s), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, ParSeNet (SplineNet), PyTorch 1.11.0, Torch-CCL 1.2.0, IPEX 1.10.0, MKL (20220804), oneDNN (v2.6.0)

CosmoFlow (training on 8192 image batches)

3rd Gen Intel® Xeon® Scalable Processor 8380 : Test by Intel as of 06/07/2022. 1-node, 2x Intel® Xeon® Scalable Processor 8380, 40 cores, HT On, Turbo On, Total Memory 512 GB (16 slots/ 32 GB/ 3200 MHz, DDR4), BIOS SE5C6200.86B.0022.D64.2105220049, ucode 0xd0002b1, OS Red Hat Enterprise Linux 8.5 (Ootpa), kernel 4.18.0-348.7.1.el8_5.x86_64, https://github.com/mlcommons/hpc/tree/main/cosmoflow, AVX-512, FP32, Tensorflow 2.9.0, horovod 0.23.0, keras 2.6.0, oneCCL-2021.4, oneAPI MPI 2021.4.0, ppn=8, LBS=16, ~25GB data, 16 epochs, Python 3.8

Intel® Xeon® 8480+ (AVX-512 FP32): Test by Intel as of 10/18/2022. 1 node, 2x Intel® Xeon® Xeon 8480+, HT On, Turbo On, Total Memory 512 GB (16 slots/ 32 GB/ 4800 MHz, DDR5), BIOS EGSDCRB1.86B.0083.D22.2206290535, ucode 0xaa0000a0, CentOS Stream 8, kernel 4.18.0-365.el8.x86_64, https://github.com/mlcommons/hpc/tree/main/cosmoflow, AVX-512, FP32, Tensorflow 2.6.0, horovod 0.23, keras 2.6.0, oneCCL 2021.5, ppn=8, LBS=16, ~25GB data, 16 epochs, Python 3.8

Intel® Xeon® Processor Max Series HBM (AVX-512 FP32): Test by Intel as of 10/18/2022. 1 node, 2x Intel® Xeon® Max 9480, HT On, Turbo On, Total Memory 128 HBM and 512 GB DDR (16 slots/ 32 GB/ 4800 MHz), BIOS SE5C7411.86B.8424.D03.2208100444, ucode  0x2c000020, CentOS Stream 8, kernel 5.19.0-rc6.0712.intel_next.1.x86_64+server, https://github.com/mlcommons/hpc/tree/main/cosmoflow, AVX-512, FP32, TensorFlow 2.6.0, horovod 0.23.0, keras 2.6.0, oneCCL 2021.5, ppn=8, LBS=16, ~25GB data, 16 epochs, Python 3.8 

Intel® Xeon® 8480+ (AMX BF16):  Test by Intel as of 10/18/2022. 1node, 2x Intel® Xeon® Platinum 8480+, HT On, Turbo On, Total Memory 512 GB (16 slots/ 32 GB/ 4800 MHz, DDR5), BIOS EGSDCRB1.86B.0083.D22.2206290535, ucode 0xaa0000a0, CentOS Stream 8, kernel 4.18.0-365.el8.x86_64, https://github.com/mlcommons/hpc/tree/main/cosmoflow, AMX, BF16, Tensorflow 2.9.1, horovod 0.24.3, keras 2.9.0.dev2022021708, oneCCL 2021.5, ppn=8, LBS=16, ~25GB data, 16 epochs, Python 3.8

Intel® Xeon® Max 9480 (AMX BF16): Test by Intel as of 10/18/2022. 1 node, 2x Intel® Xeon® Max 9480, HT On, Turbo On, Total Memory 128 HBM and 512 GB DDR (16 slots/ 32 GB/ 4800 MHz), BIOS SE5C7411.86B.8424.D03.2208100444, ucode  0x2c000020, CentOS Stream 8, kernel 5.19.0-rc6.0712.intel_next.1.x86_64+server, https://github.com/mlcommons/hpc/tree/main/cosmoflow, AMX, BF16, TensorFlow 2.9.1, horovod 0.24.0, keras 2.9.0.dev2022021708, oneCCL 2021.5, ppn=8, LBS=16, ~25GB data, 16 epochs, Python 3.9

DeepCAM

Intel® Xeon® Scalable Processor  8380: Test by Intel as of 04/07/2022. 1-node, 2x Intel® Xeon® 8380 processor, HT On, Turbo Off, Total Memory 512 GB (16 slots/ 32 GB/ 3200 MHz, DDR4), BIOS SE5C6200.86B.0022.D64.2105220049, ucode 0xd0002b1, OS Red Hat Enterprise Linux 8.5 (Ootpa), kernel 4.18.0-348.7.1.el8_5.x86_64, compiler gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-4), https://github.com/mlcommons/hpc/tree/main/deepcam, torch1.11.0a0+git13cdb98, torch-1.11.0a0+git13cdb98-cp38-cp38-linux_x86_64.whl, torch_ccl-1.2.0+44e473a-cp38-cp38-linux_x86_64.whl, intel_extension_for_pytorch-1.10.0+cpu-cp38-cp38-linux_x86_64.whl (AVX-512), Intel MPI 2021.5, ppn=8, LBS=16, ~64GB data, 16 epochs, Python3.8

Intel® Xeon® Max 9480 (Cache Mode) AVX-512: Test by Intel as of 05/25/2022. 1-node, 2x Intel® Xeon® Max 9480, HT On,Turbo Off, Total Memory 128GB HBM and 1TB (16 slots/ 64 GB/ 4800 MHz, DDR5), Cluster Mode: SNC4, BIOS EGSDCRB1.86B.0080.D05.2205081330, ucode 0x8f000320, OS CentOS Stream 8, kernel 5.18.0-0523.intel_next.1.x86_64+server, compiler gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-10, https://github.com/mlcommons/hpc/tree/main/deepcam, torch1.11.0a0+git13cdb98, AVX-512, FP32, torch-1.11.0a0+git13cdb98-cp38-cp38-linux_x86_64.whl, torch_ccl-1.2.0+44e473a-cp38-cp38-linux_x86_64.whl, intel_extension_for_pytorch-1.10.0+cpu-cp38-cp38-linux_x86_64.whl (AVX-512), Intel MPI 2021.5, ppn=8, LBS=16, ~64GB data, 16 epochs, Python3.8

Intel® Xeon® Max 9480 (Cache Mode) BF16/AMX: Test by Intel as of 05/25/2022. 1-node, 2x Intel® Xeon® Max 9480 , HT On, Turbo Off, Total Memory 128GB HBM and 1TB (16 slots/ 64 GB/ 4800 MHz, DDR5), Cluster Mode: SNC4, BIOS EGSDCRB1.86B.0080.D05.2205081330, ucode 0x8f000320, OS CentOS Stream 8, kernel 5.18.0-0523.intel_next.1.x86_64+server, compiler gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-10), https://github.com/mlcommons/hpc/tree/main/deepcam, torch1.11.0a0+git13cdb98, AVX-512 FP32, torch-1.11.0a0+git13cdb98-cp38-cp38-linux_x86_64.whl, torch_ccl-1.2.0+44e473a-cp38-cp38-linux_x86_64.whl, intel_extension_for_pytorch-1.10.0+cpu-cp38-cp38-linux_x86_64.whl (AVX-512, AMX, BFloat16 Enabled), Intel MPI 2021.5, ppn=8, LBS=16, ~64GB data, 16 epochs, Python3.8

Intel® Xeon® 8480+s Mulit-Node cluster: Test by Intel as of 04/09/2022. 16-nodes Cluster, 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, Total Memory 256 GB (16 slots/ 16 GB/ 4800 MHz, DDR5), BIOS Intel SE5C6301.86B.6712.D23.2111241351, ucode 0x8d000360, OS Red Hat Enterprise Linux 8.4 (Ootpa), kernel 4.18.0-305.el8.x86_64, compiler gcc (GCC) 8.4.1 20200928 (Red Hat 8.4.1-1), https://github.com/mlcommons/hpc/tree/main/deepcam, torch1.11.0a0+git13cdb98 AVX-512, FP32, torch-1.11.0a0+git13cdb98-cp38-cp38-linux_x86_64.whl, torch_ccl-1.2.0+44e473a-cp38-cp38-linux_x86_64.whl, intel_extension_for_pytorch-1.10.0+cpu-cp38-cp38-linux_x86_64.whl (AVX-512), Intel MPI 2021.5, ppn=4, LBS=16, ~1024GB data, 16 epochs, Python3.8

WRF4.4 – CONUS-2.5km

Intel Xeon 8360Y: Test by Intel as of 2/9/23, 2x Intel Xeon 8360Y, HT On, Turbo On, NUMA configuration SNC2, 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, WRF v4.4  built with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags ”-ip -O3 -xCORE-AVX512 -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low -w -ftz -align array64byte -fno-alias -fimf-use-svml=true -inline-max-size=12000 -inline-max-total-size=30000 -vec-threshold0 -qno-opt-dynamic-align ”.  HDR Fabric

Intel Xeon 8480+: Test by Intel as of 2/9/23, 2x Intel Xeon 8480+, HT On, Turbo On, NUMA configuration SNC4, 512 GB (16x32GB 4800MT/s, Dual-Rank), BIOS Version SE5C7411.86B.8713.D03.2209091345, ucode revision=0x2b000070, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, WRF v4.4 built with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-ip -O3 -xCORE-AVX512 -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low -w -ftz -align array64byte -fno-alias -fimf-use-svml=true -inline-max-size=12000 -inline-max-total-size=30000 -vec-threshold0 -qno-opt-dynamic-align  ”.  HDR Fabric

Intel Xeon Max 9480: Test by Intel as of 2/9/23, 2x Intel® Xeon® Max 9480, HT ON, Turbo ON, NUMA configuration SNC4, 128 GB HBM2e at 3200 MHz and 512 GB DDR5-4800, BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, WRF v4.4 built with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-ip -O3 -xCORE-AVX512 -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low -w -ftz -align array64byte -fno-alias -fimf-use-svml=true -inline-max-size=12000 -inline-max-total-size=30000 -vec-threshold0 -qno-opt-dynamic-align ”.  HDR Fabric

ROMS (benchmark3 (2048x256x30), benchmark3 (8192x256x30))

Intel® Xeon® 8380: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, NUMA configuration SNC2, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, ROMS V4 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-ip -O3 -heap-arrays -xCORE-AVX512 -qopt-zmm-usage=high -align array64byte -fimf-use-svml=true -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low”, ROMS V4

Intel® Xeon® 8480+: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, NUMA configuration SNC4, Total Memory 512 GB (16x32GB 4800MT/s, Dual-Rank), BIOS Version SE5C7411.86B.8713.D03.2209091345, ucode revision=0x2b000070, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, ROMS V4 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-ip -O3 -heap-arrays -xCORE-AVX512 -qopt-zmm-usage=high -align array64byte -fimf-use-svml=true -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low”, ROMS V4

Intel® Xeon® Max 9480: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® Max 9480, HT ON, Turbo ON, NUMA configuration SNC4, Total Memory 128 GB (HBM2e at 3200 MHz), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, ROMS V4 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-ip -O3 -heap-arrays -xCORE-AVX512 -qopt-zmm-usage=high -align array64byte -fimf-use-svml=true -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low”, ROMS V4

NEMO (GYRE_PISCES_25, BENCH ORCA-1)

Intel® Xeon® 8380: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, NUMA configuration SNC2, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, NEMO v4.2 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags ”-i4 -r8 -O3 -fno-alias -march=core-avx2 -fp-model fast=2 -no-prec-div -no-prec-sqrt -align array64byte -fimf-use-svml=true”

Intel® Xeon® Max 9480: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® Max 9480, HT ON, Turbo ON, NUMA configuration SNC4, Total Memory 128 GB (HBM2e at 3200 MHz), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, NEMO v4.2 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-i4 -r8 -O3 -fno-alias -march=core-avx2 -fp-model fast=2 -no-prec-div -no-prec-sqrt -align array64byte -fimf-use-svml=true”.

Ansys Fluent

Intel Xeon 8380: Test by Intel as of 08/24/2022, 2x Intel® Xeon®  8380, HT ON, Turbo ON, Hemisphere, 256 GB DDR4-3200, BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode 0xd000375,  Rocky Linux 8.7, kernel version 4.18.0-372.32.1.el8_6.crt2.x86_64, Ansys Fluent 2022R1 . HDR Fabric

Intel Xeon 8480+: Test by Intel as of 2/11/2023, 2x Intel® Xeon® 8480+, HT ON, Turbo ON, SNC4 Mode, 512 GB DDR5-4800, BIOS Version SE5C7411.86B.8901.D03.2210131232, ucode 0x2b0000a1,  Rocky Linux 8.7, kernel version 4.18.0-372.32.1.el8_6.crt2.x86_64, Ansys Fluent 2022R1. HDR Fabric

Intel Xeon Max 9480: Test by Intel as of 02/15/2023, 2x Intel Xeon Max 9480, HT ON, Turbo ON, SNC4, SNC4 and Fake Numa for Cache Mode runs, 128 GB HBM2e at 3200 MHz and 512 GB DDR5-4800,  BIOS Version SE5C7411.86B.9409.D04.2212261349, ucode 0xac000100,  Rocky Linux 8.7, kernel version 4.18.0-372.32.1.el8_6.crt2.x86_64, Ansys Fluent 2022R1. HDR Fabric

Ansys LS-DYNA (ODB-10M)

Intel® Xeon® 8380: Test by Intel as of 10/7/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, Total Memory 256 GB (16x16GB 3200MT/s DDR4), BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, LS-DYNA R11

Intel® Xeon® 8480+: Test by Intel as of ww41’22. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, SNC4, Total Memory 512 GB (16x32GB 4800MT/s, DDR5), BIOS Version SE5C7411.86B.8713.D03.2209091345, ucode revision=0x2b000070, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, LS-DYNA R11

Intel® Xeon® Max 9480: Test by Intel as of ww36’22. 1-node, 2x   Intel® Xeon® Max 9480, HT

Ansys Mechanical (V22iter-1, V22iter-2, V22iter-3, V22iter-4, V22direct-1, V22direct-2, V22direct-3)

Intel® Xeon® 8380: Test by Intel as of 08/24/2022. 1-node, 2x Intel® Xeon® 8380, HT ON, Turbo ON, Quad, Total Memory 256 GB, BIOS Version SE5C6200.86B.0020.P23.2103261309, ucode 0xd000270, Rocky Linux 8.6, kernel version 4.18.0-372.19.1.el8_6.crt1.x86_64, Ansys Mechanical 2022 R2

AMD EPYC 7763: Test by Intel as of 8/24/2022. 1-node, 2x AMD EPYC 7763, HT On, Turbo On, NPS2,Total Memory 512 GB, BIOS ver. Ver 2.1 Rev 5.22, ucode 0xa001144, Rocky Linux 8.6, kernel version 4.18.0-372.19.1.el8_6.crt1.x86_64, Ansys Mechanical 2022 R2

AMD EPYC 7773X: Test by Intel as of 8/24/2022. 1-node, 2x AMD EPYC 7773X, HT On, Turbo On, NPS4,Total Memory 512 GB, BIOS ver. M10, ucode 0xa001229, CentOS Stream 8, kernel version 4.18.0-383.el8.x86_6, Ansys Mechanical 2022 R2

Intel® Xeon® 8480+: Test by Intel as of 09/02/2022. 1-node, 2x Intel® Xeon® 8480+, HT ON, Turbo ON, SNC4, Total Memory 512 GB DDR5 4800 MT/s, BIOS Version EGSDCRB1.86B.0083.D22.2206290535, ucode 0xaa0000a0,  CentOS Stream 8, kernel version 4.18.0-365.el8.x86_64, Ansys Mechanical 2022 R2

Intel® Xeon® Max 9480: Test by Intel as of 08/31/2022. 1-node, 2x Intel® Xeon® Max 9480, HT On, Turbo ON, SNC4, Total Memory 512 GB DDR5 4800 MT/s, 128 GB HBM in Cache Mode (HBM2e at 3200 MHz), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode 2c000020, CentOS Stream 8, kernel version 5.19.0-rc6.0712.intel_next.1.x86_64+server, Ansys Mechanical 2022 R2

Altair AcuSolve (HQ Model)

Intel® Xeon® 8380: Test by Intel as of 09/28/2022. 1-node, 2x Intel® Xeon® 8380, HT ON, Turbo ON, Quad, Total Memory 256 GB, BIOS Version SE5C6200.86B.0020.P23.2103261309, ucode 0xd000270, Rocky Linux 8.6, kernel version 4.18.0-372.19.1.el8_6.crt1.x86_64, Altair AcuSolve 2021R2

Intel® Xeon® 6346: Test by Intel as of 10/08/2022. 4-nodes connected via HDR-200, 2x Intel® Xeon® 6346, 16 cores, HT ON, Turbo ON, Quad, Total Memory 256 GB, BIOS Version SE5C6200.86B.0020.P23.2103261309, ucode 0xd000270,  Rocky Linux 8.6, kernel version 4.18.0-372.19.1.el8_6.crt1.x86_64, Altair AcuSolve 2021R2

Intel® Xeon® 8480+: Test by Intel as of 09/28/2022. 1-node, 2x Intel® Xeon® 8480+, HT ON, Turbo ON, SNC4, Total Memory 512 GB, BIOS Version EGSDCRB1.86B.0083.D22.2206290535, ucode 0xaa0000a0,  CentOS Stream 8, kernel version 4.18.0-365.el8.x86_64, Altair AcuSove 2021R2

Intel® Xeon® Max 9480: Test by Intel as of 10/03/2022. 1-node, 2x Intel® Xeon® Max 9480, HT ON, Turbo ON, SNC4, Total Memory 128 GB (HBM2e at 3200 MHz), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode 2c000020, CentOS Stream 8, kernel version 5.19.0-rc6.0712.intel_next.1.x86_64+server, Altair AcuSolve 2021R2

OpenFOAM (Geomean of Motorbike 20M, Motorbike 42M)

Intel® Xeon® 8380: Test by Intel as of 9/2/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C6200.86B.0020.P23.2103261309, ucode revision=0xd000270, Rocky Linux 8.6, Linux version 4.18.0-372.19.1.el8_6.crt1.x86_64, OpenFOAM 8, Motorbike 20M @ 250 iterations, Motorbike 42M @ 250 iterations

Intel® Xeon® 8480+: Test by Intel as of 9/2/2022. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, Total Memory 512 GB (16x32GB 4800MT/s, Dual-Rank), BIOS Version EGSDCRB1.86B.0083.D22.2206290535, ucode revision=0xaa0000a0, CentOS Stream 8, Linux version 4.18.0-365.el8.x86_64, OpenFOAM 8, Motorbike 20M @ 250 iterations, Motorbike 42M @ 250 iterations

Intel® Xeon® Max 9480: Test by Intel as of 9/2/2022. 1-node, 2x Intel® Xeon® Max 9480, HT On, Turbo On, SNC4, Total Memory 128 GB (8x16GB HBM2 3200MT/s), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, OpenFOAM 8, Motorbike 20M @ 250 iterations, Motorbike 42M @ 250 iterations

MPAS-A (MPAS-A V7.3 60-km dynamical core)

Intel® Xeon® 8380: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, NUMA configuration SNC2, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, MPAS-A V7.3 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-O3 -march=core-avx2 -convert big_endian -free -align array64byte -fimf-use-svml=true -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low”, MPAS-A V7.3

Intel® Xeon® 8480+: Test by Intel as of 10/12/2022. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, NUMA configuration SNC4, Total Memory 512 GB (16x32GB 4800MT/s, Dual-Rank), BIOS Version SE5C7411.86B.8713.D03.2209091345, ucode revision=0x2b000070, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, MPAS-A V7.3 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-O3 -march=core-avx2 -convert big_endian -free -align array64byte -fimf-use-svml=true -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low”, MPAS-A V7.3

Intel® Xeon® Max 9480: Test by Intel as of 10/12/22. 1-node, 2x Intel® Xeon® Max 9480, HT ON, Turbo ON, NUMA configuration SNC4, Total Memory 128 GB (HBM2e at 3200 MHz), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, MPAS-A V7.3 build with Intel® Fortran Compiler Classic and Intel® MPI from 2022.3 Intel® oneAPI HPC Toolkit with compiler flags “-O3 -march=core-avx2 -convert big_endian -free -align array64byte -fimf-use-svml=true -fp-model fast=2 -no-prec-div -no-prec-sqrt -fimf-precision=low”, MPAS-A V7.3

GROMACS (benchMEM​, benchPEP​, benchPEP-h, benchRIB​, hecbiosim-3m​, hecbiosim-465k​, hecbiosim-61k​, ion_channel_pme_large​, lignocellulose_rf_large​, rnase_cubic​, stmv​, water1.5M_pme_large​, water1.5M_rf_large)

Intel® Xeon® 8380: Test by Intel as of 10/7/2022. 1-node, 2x Intel® Xeon® 8380 CPU, HT On, Turbo On, NUMA configuration SNC2, Total Memory 256 GB (16x16GB 3200MT/s, Dual-Rank), BIOS Version SE5C620.86B.01.01.0006.2207150335, ucode revision=0xd000375, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, Converge GROMACS v2021.4_SP

Intel® Xeon® 8480+: Test by Intel as of 10/7/2022. 1-node, 2x Intel® Xeon® 8480+, HT On, Turbo On, SNC4, Total Memory 512 GB (16x32GB 4800MT/s, DDR5), BIOS Version SE5C7411.86B.8713.D03.2209091345, ucode revision=0x2b000070, Rocky Linux 8.6, Linux version 4.18.0-372.26.1.el8_6.crt1.x86_64, GROMACS v2021.4_SP

Intel® Xeon® Max 9480: Test by Intel as of 9/2/2022. 1-node, 2x Intel® Xeon® Max 9480, HT ON, Turbo ON, NUMA configuration SNC4, Total Memory 128 GB (HBM2e at 3200 MHz), BIOS Version SE5C7411.86B.8424.D03.2208100444, ucode revision=0x2c000020, CentOS Stream 8, Linux version 5.19.0-rc6.0712.intel_next.1.x86_64+server, GROMACS v2021.4_SP

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