From 9abfa9b2ee910c45093c11bcc637449c32f00253 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Filip=20Stan=C4=9Bk?= <filip.stanek@vsb.cz> Date: Wed, 28 Jul 2021 10:07:55 +0200 Subject: [PATCH] Update compute-nodes.md --- docs.it4i/karolina/compute-nodes.md | 19 ++++++++----------- 1 file changed, 8 insertions(+), 11 deletions(-) diff --git a/docs.it4i/karolina/compute-nodes.md b/docs.it4i/karolina/compute-nodes.md index f77cb2372..5de3b3e67 100644 --- a/docs.it4i/karolina/compute-nodes.md +++ b/docs.it4i/karolina/compute-nodes.md @@ -11,7 +11,6 @@ Standard compute nodes without accelerators (such as GPUs or FPGAs) are based on * 2x AMD EPYC™ 7H12, 64-core, 2.6 GHz processors per node * 256 GB DDR4 3200MT/s of physical memory per node * 5,324.8 GFLOP/s per compute node -* 1x 100 Gb/s Ethernet * 1x 100 Gb/s IB port * Cn[001-720] @@ -25,9 +24,8 @@ Accelerated compute nodes deliver most of the compute power usable for HPC as we * 9,216 cores in total * 2x AMD EPYC™ 7763, 64-core, 2.45 GHz processors per node * 1024 GB DDR4 3200MT/s of physical memory per node -* 8x GPU accelerator NVIDIA A100 per node +* 8x GPU accelerator NVIDIA A100 per node, 320GB HBM2 memory per node * 5,017.6 GFLOP/s per compute node -* 4x 200 Gb/s Ethernet * 4x 200 Gb/s IB port * Acn[01-72] @@ -41,10 +39,9 @@ Data analytics compute node is oriented on supporting huge memory jobs by implem * 768 cores in total * 32x Intel® Xeon® Platinum, 24-core, 2.9 GHz, 205W * 24 TB DDR4 2993MT/s of physical memory per node -* 2x 200 Gb/s Ethernet * 2x 200 Gb/s IB port * 71.2704 TFLOP/s -* DAcn1 +* Sdf1  @@ -58,17 +55,17 @@ Cloud compute nodes support both the research and operation of the Infrastructur * 256 GB DDR4 3200MT/s of physical memory per node * HPE ProLiant XL225n Gen10 Plus servers * 5,324.8 GFLOP/s per compute node -* 1x 100 Gb/s Ethernet +* 2x 10 Gb/s Ethernet * 1x 100 Gb/s IB port * CLn[01-36] ## Compute Node Summary -| Node type | Count | Range | Memory | Cores | Queues (?) | -| ---------------------------- | ----- | ----------- | ------ | ----------- | -------------------------- | +| Node type | Count | Range | Memory | Cores | Queues (?) | +| ---------------------------- | ----- | ------------ | ------- | -------------- | -------------------------- | | Nodes without an accelerator | 720 | Cn[001-720] | 256 GB | 128 @ 2.6 GHz | qexp, qprod, qlong, qfree | -| Nodes with a GPU accelerator | 72 | Acn[01-72] | 1024 GB | 64 @ 2.45 GHz | qnvidia | -| Data analytics nodes | 1 | DAcn1 | 24 TB | 768 @ 2.9 GHz | qfat | +| Nodes with a GPU accelerator | 72 | Acn[01-72] | 1024 GB | 64 @ 2.45 GHz | qnvidia | +| Data analytics nodes | 1 | Sdf1 | 24 TB | 768 @ 2.9 GHz | qfat | | Cloud partiton | 36 | CLn[01-36] | 256 GB | 128 @ 2.6 GHz | | ## Processor Architecture @@ -86,7 +83,7 @@ EPYC™ 7H12 is a 64-bit 64-core x86 server microprocessor designed and introduc * **L1D Cache**: 2 MiB, 64x32 KiB, 8-way set associative * **L2 Cache**: 32 MiB, 64x512 KiB, 8-way set associative, write-back * **L3 Cache**: 256 MiB, 16x16 MiB -* **Instructions**(?): x86-64, MOVBE, MMX, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, POPCNT, AVX, AVX2, AES, PCLMUL, FSGSBASE, RDRND, FMA3, F16C, BMI, BMI2, VT-x, VT-d, TXT, TSX, RDSEED, ADCX, PREFETCHW, CLFLUSHOPT, XSAVE, SGX, MPX, AVX-512 (New instructions for [Vector Neural Network Instructions][c]) +* **Instructions**: x86-16, x86-32, x86-64, MMX, EMMX, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, SSE4a, AVX, AVX2, AES, CLMUL, RdRanD, FMA3, F16C, ABM, BMI1, BMI2, AMD-Vi, AMD-V, SHA, ADX, Real, Protected, SMM, FPU, NX, SMT, SME, TSME, SEV, SenseMI, Boost2 * **Frequency**: 2.6 GHz * **Max turbo**: 3.3 GHz * **Process**: 7 nm, 14 nm -- GitLab