COMPUTE ATLAS Supercomputer supply-chain graph
1153 systems 482 sites Sourced data

Supercomputers/Systems/PARAM Siddhi-AI

India · operational · ai training

PARAM Siddhi-AI

Also known as PARAM Siddhi

Operated by C-DAC at C-DAC (Pashan, Pune) .

Phase 1 seed dataset, compiled by hand. These rows were built from public operator, laboratory and vendor sources. A mechanical second-reader pass has since fetched every cited source: 1092 of 1153 systems have a readable citation that names them, and 40 are genuinely weakly sourced. Every claim carries its source and a confidence tier. Treat anything below verified as a lead, not a citation.

Measured performance

Rmax
4.62 PFlop/s
HPL measured
Rpeak
5.27 PFlop/s
Rmax ÷ Rpeak
87.7%
Cores
41,664
Power
-
Per watt
- GF/W

Figures are as last publicly reported for the configuration described below, not a live measurement. Where a system was upgraded in place, the post-upgrade configuration is shown and the earlier one appears in the timeline.

What this machine is made of

One row per supplier relationship. “Supplier at build” is the company that shipped the part at the time; where that company has since been acquired, the parent it rolls up to today is shown beside it. That distinction is what makes ticker-level aggregation possible across a thirty-year dataset.

Role Part Supplier at build Quantity Confidence Source
Accelerator NVIDIA A100 SXM4 40GB
Accelerators
CUDA (Ampere GA100) · 6,912C · 1.41 GHz · 7 nm · 400 W
42 NVIDIA DGX A100 nodes, eight A100 SXM4 40GB GPUs per node
NVIDIA 336
estimated
Verified devdiscourse.comtop500.org
CPU AMD EPYC 7742 (Rome)
CPUs
x86-64 · 64C · 2.25 GHz · 7 nm · 225 W
AMD EPYC 7742 host CPUs across the 42 DGX A100 nodes; no source states the exact chip count
AMD - Verified top500.orgdevdiscourse.com
Interconnect NVIDIA InfiniBand HDR
Interconnect
Fat tree or dragonfly+ · 200 Gb/s per port · About 0.6 microseconds
Mellanox HDR InfiniBand fabric
NVIDIA - Verified top500.orgdevdiscourse.com
Operating system Ubuntu Server
Operating systems
Linux distribution · Open source, free with paid support tiers
Ubuntu 20.04.1 LTS
Canonical
- Reported top500.org

The read

C-DAC's HPC-AI system at the National PARAM Supercomputing Facility in Pune, built on NVIDIA's DGX SuperPOD reference architecture: 42 DGX A100 nodes, each with two AMD EPYC 7742 hosts and eight A100 GPUs (the only A100 SXM4 variant that existed in mid-2020, before the 80GB part shipped), linked by Mellanox HDR InfiniBand and layered with C-DAC's own HPC-AI engine, software frameworks and cloud platform. NVIDIA's own commissioning release and TOP500 independently agree on the vendor, node count, host CPU and fabric, so the tier is verified; TOP500 alone gives the exact Rmax, Rpeak and core count. It debuted 62nd on the November 2020 TOP500, India's best-ever ranking at the time, though some Indian government retrospectives round that to 63rd. From 2023 it has shared its Pune facility with the newer AIRAWAT system; C-DAC markets a combined '410 AI petaflops mixed precision' across the two machines, a figure this dataset does not reproduce since TOP500 measures each system separately.

Timeline

Public list appearances

Pointers only: rank and edition, linking to the canonical entry. We do not reproduce list tables. See sourcing policy.

Site & facility

C-DAC (Pashan, Pune)

Location
Pune, India
Commissioned
2020

Where sources disagree

We record conflicts instead of picking a winner quietly. All open questions.

Change history

Source check

We fetched this system's own citations and recorded whether each page actually mentions it. This is a corroboration signal, not a fact check, and it is published so you can see how well the sourcing holds up rather than take it on trust.

Cited sourceResultFound on the page
devdiscourse.comnames system and partNVIDIA A100 SXM4 40GB, NVIDIA InfiniBand HDR
top500.orgnames system and partNVIDIA A100 SXM4 40GB, AMD EPYC 7742 (Rome), NVIDIA InfiniBand HDR, Ubuntu Server

Checked 2026-10-09 by pnpm verify. Re-run it and the table changes with the web.

Further reading