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AI Trifecta – MLPerf Issues Latest HPC, Training, and Tiny Benchmarks
MLCommons yesterday issued its latest round of MLPerf benchmarks – for Training, HPC, and Tiny. Releasing three sets of benchmarks at the same time makes parsing the results, never an easy chor …
Quantum Annealing Pioneer D-Wave Introduces Expanded Hybrid Solver
D-Wave Systems, a pioneer in quantum annealing-based computing, today announced significant upgrades to its constrained quadratic model (CQM) hybrid solver that should make it easier to use and a …
Dell, AMD, IBM, and Strangeworks Dig into Quantum’s Future
October 27, 2022
What’s the quantum computing fuss all about? Should you jump into the game or run as fast as you can away from it? A fascinating panel with committed quantum players, IBM and Strangeworks, and traditional computing powerhouses, Dell (systems) and AMD (chips), tackled this topic at the HPC + AI on Wall Street conference held earlier this... Read more…
CEO Jack Hidary on SandboxAQ’s Ambitions and Near-term Milestones
October 18, 2022
Spun out from Google last March, SandboxAQ is a fascinating, well-funded start-up targeting the intersection of AI and quantum technology. “As the world enter Read more…
Nvidia, Qualcomm Shine in MLPerf Inference; Intel’s Sapphire Rapids Makes an Appearance.
September 8, 2022
The steady maturation of MLCommons/MLPerf as an AI benchmarking tool was apparent in today’s release of MLPerf v2.1 Inference results. Twenty-one organization Read more…
AWS Takes the Short and Long View of Quantum Computing
August 30, 2022
It is perhaps not surprising that the big cloud providers – a poor term really – have jumped into quantum computing. Amazon, Microsoft Azure, Google, and th Read more…
Chip Pioneers to Battle it out in Modern RISC-V AI Chips
August 25, 2022
Some chip pioneers from the 1980s are raising the ante in modern chip design with new opportunities provided by artificial intelligence and the open-source RISC-V architecture. Untether AI, which was co-founded by an analog and mixed signal chip pioneer Martin Snelgrove, released a new AI inferencing chip called Boqueria, which has more than 1,400 optimized RISC-V processors. That chip will compete... Read more…
AQT Reports Optimizing SWAP Networks for Quantum Computing
August 4, 2022
A research partnership at the Advanced Quantum Testbed (AQT) at Lawrence Berkeley National Laboratory (Berkeley Lab) and Chicago-based Super.tech (acquired by ColdQuanta in May 2022) has demonstrated how to optimize the execution of the ZZ SWAP network protocol, important to quantum computing. The team also introduced a new technique... Read more…
Nvidia Dives Deeper into Quantum, Announces QODA Programming Platform
July 12, 2022
GPU and accelerated-computing powerhouse Nvidia today announced a new programming platform – NVIDIA Quantum Optimized Device Architecture (QODA) – targeting development and management of applications run on hybrid classical-quantum systems. QODA joins cuQuantum, Nvidia’s quantum simulation SDK for use on GPU-accelerated systems. Unlike cuQuantum... Read more…
Solving Heterogeneous Programming Challenges with Python, Today
June 30, 2022
You may be surprised how ready Python is for heterogeneous programming, and how easy it is to use today. Our first three articles about heterogeneous programming focused primarily on C++ as we ponder “how to enable programming in the face of an explosion of hardware diversity that is coming?” For a refresher on what motivates this question... Read more…
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Whitepaper
Porting CUDA Applications to Run on AMD GPUs
Giving developers the ability to write code once and use it on different platforms is important. Organizations are increasingly moving to open source and open standard solutions which can aid in code portability. AMD developed a porting solution that allows developers to port proprietary NVIDIA® CUDA® code to run on AMD graphic processing units (GPUs).
This paper describes the AMD ROCm™ open software platform which provides porting tools to convert NVIDIA CUDA code to AMD native open-source Heterogeneous Computing Interface for Portability (HIP) that can run on AMD Instinct™ accelerator hardware. The AMD solution addresses performance and portability needs of artificial intelligence (AI), machine learning (ML) and high performance computing (HPC) for application developers. Using the AMD ROCm platform, developers can port their GPU applications to run on AMD Instinct accelerators with very minimal changes to be able to run their code in both NVIDIA and AMD environments.
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QCT HPC BeeGFS Storage: A Performance Environment for I/O Intensive Workloads
A workload-driven system capable of running HPC/AI workloads is more important than ever. Organizations face many challenges when building a system capable of running HPC and AI workloads. There are also many complexities in system design and integration. Building a workload driven solution requires expertise and domain knowledge that organizational staff may not possess.
This paper describes how Quanta Cloud Technology (QCT), a long-time Intel® partner, developed the Taiwania 2 and Taiwania 3 supercomputers to meet the research needs of the Taiwan’s academic, industrial, and enterprise users. The Taiwan National Center for High-Performance Computing (NCHC) selected QCT for their expertise in building HPC/AI supercomputers and providing worldwide end-to-end support for solutions from system design, through integration, benchmarking and installation for end users and system integrators to ensure customer success.
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