500X Increase In Compute Performance Scalable Compute & Memory Packaging & Interconnect For Density & Scale Full Software Stack/Programming Model

This article consists only of a collection of slides from the author's conference presentation.

The Intel core microarchitecture is a new foundation for Intel architecture-based desktop, mobile and mainstream server multi-core processors. Designed for efficiency and optimised performance across a range of market segments and power envelopes.

The modern graphics processing unit (GPU) is the result of 40 years of evolution of hardware to accelerate graphics processing operations. It represents the convergence of support for multiple market segments: computer-aided design, medical imaging, digital content creation, document and presentation applications, and entertainment applications. The exceptional performance characteristics of the GPU make it an attractive target for other application domains. We examine some of this evolution, look at the structure of a modern GPU, and discuss how graphics processing exploits this structure and how nongraphical applications can take advantage of this capability. We discuss some of the technical and market issues around broader adoption of this technology.

We present a system architecture for the 4 th generation of PC-class programmable graphics processing units (GPUs). The new pipeline features significant additions and changes to the prior generation pipeline including a new programmable stage capable of generating additional primitives and streaming primitive data to memory, an expanded, common feature set for all of the programmable stages, generalizations to vertex and image memory resources, and new storage formats. We also describe structural modifications to the API, runtime, and shading language to complement the new pipeline. We motivate the design with descriptions of frequently encountered obstacles in current systems. Throughout the paper we present rationale behind prominent design choices and alternatives that were ultimately rejected, drawing on insights collected during a multi-year collaboration with application developers and hardware designers.

Applications of virtual reality (VR) and augmented reality (AR) in medicine require real-time visualization and modeling of large three-dimensional data sets. Consequently, these applications require powerful computation, extensive high-bandwidth memory, and fast communication links. In the past, the manufacturers of medical imaging equipment produced their own special-purpose proprietary hardware for image processing and solid graphics. Due to the developments in computer hardware in general and in graphics accelerators in particular, there is a trend toward replacing the proprietary hardware off-the-shelf (OTS) equipment. Computer graphics itself has advanced in its quest for realism. Generic algorithms such as shading, texture mapping, and volume rendering have been developed to meet the resultant ever increasing requirements. Advances in both the OTS CPU and graphics hardware have enabled real-time implementations of these algorithms, thereby facilitating many of the medical VR/AR applications used today. The development of graphics libraries such as OpenGL has also been an important factor. These libraries provide an underlying portable software platform that optimizes the utilization of the available graphics hardware. OpenGL has become a standard graphics application programming interface, particularly for graphics-intensive applications, and more and more OTS systems provide hardware implementations of OpenGL commands. The review paper follows the evolution of these technologies and examines their crucial role in enabling the appearance of the current VR/AR applications in medicine and provides a look at current trends and future possibilities.