high performance computing on graphics processing units: hgpu.org

Adapting applications to optimally utilize available hardware is no mean feat: the plethora of choices for optimization techniques are infeasible to maximize manually. To this end, auto-tuning frameworks are used to automate this task, which in turn use optimization algorithms to efficiently search the vast searchspaces. However, there is a lack of comparability in studies […]

Nowadays, a variety of applications, including automated factories, autonomous vehicles, and Cyber Physical Systems (CPS), are experiencing significant growth. Given the diverse range of challenges that must be addressed, such as real-time management and visualization of a factory’s current state through a 3D digital twin, trajectory calculation within autonomous vehicles, visualizing Human Machine Interfaces (HMI), […]

Molecular dynamics simulations are one of the methods in scientific computing that benefit from GPU acceleration. For those devices, SYCL is a promising API for writing portable codes. In this paper, we present the case study of "HAL’s MD package" that has been successfully migrated from CUDA to SYCL. We describe the different strategies that […]

In recent work, we have shown that NVIDIA’s raytracing cores on RTX video cards can be exploited to realize hardware-accelerated lookups for GPU-resident database indexes. On a high level, the concept materializes all keys as triangles in a 3D scene and indexes them. Lookups are performed by firing rays into the scene and utilizing the […]

Matrix multiplication is a cornerstone operation in a wide array of scientific fields, including machine learning and computer graphics. The standard algorithm for matrix multiplication has a complexity of O(n3) for n×n matrices. Strassen’s algorithm improves this to O(n2.807), but its practicality is limited for small to medium matrix sizes due to the large number […]

This paper introduces Helix, a distributed system for high-throughput, low-latency large language model (LLM) serving on heterogeneous GPU clusters. A key idea behind Helix is to formulate inference computation of LLMs over heterogeneous GPUs and network connections as a max-flow problem for a directed, weighted graph, whose nodes represent GPU instances and edges capture both […]

While Field-Programmable Gate Arrays (FPGAs) exist in many design configurations throughout the data center, cloud, and edge, the promise of performance and flexibility offered by the FPGA often remains unrealized for lack of hardware design expertise, with most computation remaining in fixed hardware such as CPUs, GPUs, and ASICs e.g. tensor processors. Identifying programmability as […]

Cloud computing increasingly handles confidential data, like private inference and query databases. Two strategies are used for secure computation: (1) employing CPU Trusted Execution Environments (TEEs) like AMD SEV, Intel SGX, or ARM TrustZone, and (2) utilizing emerging cryptographic methods like Fully Homomorphic Encryption (FHE) with libraries such as HElib, Microsoft SEAL, and PALISADE. To […]

Matrix multiplication is fundamental in the backpropagation algorithm used to train deep neural network models. Libraries like Intel’s MKL or NVIDIA’s cuBLAS implemented new and optimized matrix multiplication techniques that increase performance and reduce computational costs. These techniques can also be implemented in CUDA and SYCL and functions with AVX2 and AVX512 instructions, which have […]

We present a GPU implementation of vertex-patch smoothers for higher order finite element methods in two and three dimensions. Analysis shows that they are not memory bound with respect to GPU DRAM, but with respect to on-chip scratchpad memory. Multigrid operations are optimized through localization and reorganized local operations in on-chip memory, achieving minimal global […]

Graphics processing units (GPUs) are the hardware engines driving the AI revolution. Large language model (LLM)-powered generative AI (GenAI) became mainstream with the public release of OpenAI’s ChatGPT. AI usage has given rise to innovative AI-powered applications for businesses, productivity, image generation, video generation, data analysis, and social media, among others. Powering AI applications are […]

This paper explores practical aspects of using a high-level functional language for GPU-based arithmetic on “midsize” integers. By this we mean integers of up to about a quarter million bits, which is sufficient for most practical purposes. The goal is to understand whether it is possible to support efficient nested-parallel programs with a small, flexible […]