High-performance computing (HPC) applications are increasingly executed in heterogeneous environments, introducing new challenges for programming and software portability. SYCL has emerged as a leading model designed to simplify heterogeneous programming and make it more accessible to developers. Intended as a single-source, cross-platform parallel programming framework, SYCL promises portability, productivity, and performance across a variety of architectures. However, these goals have not been consistently defined or realized, leaving developers with varying expectations. This paper addresses this gap by evaluating SYCL from the perspective of application developers. We analyze whether SYCL meets essential criteria for cross-platform development, including code portability, development productivity, and runtime efficiency. Our evaluation draws on benchmarks and illustrative examples and focuses on SYCL's memory management and parallelism abstractions. We provide detailed comparisons between Unified Shared Memory (USM) and buffer-accessor approaches, as well as between NDRange and hierarchical kernel models. In addition to presenting our own benchmark results on Intel platforms, we synthesize findings from recent studies across multiple SYCL implementations and compilers. Our results expose key limitations and inconsistencies in current SYCL implementations and offer insights into the steps needed to improve the framework's reliability and cross-platform usability.

翻译：高性能计算（HPC）应用日益在异构环境中执行，这给编程和软件可移植性带来了新挑战。SYCL作为一种旨在简化异构编程并使之更易为开发者所用的领先模型应运而生。作为一款单源、跨平台并行编程框架，SYCL承诺在多种架构上实现可移植性、生产效率和性能。然而，这些目标尚未得到一致定义或实现，导致开发者持有不同期望。本文从应用开发者的角度评估SYCL，以填补这一空白。我们分析了SYCL是否满足跨平台开发的关键标准，包括代码可移植性、开发生产效率和运行时效率。我们的评估基于基准测试和示例实例，重点考察SYCL的内存管理和并行抽象机制。我们详细比较了统一共享内存（USM）与缓冲-访问器方法，以及NDRange与分层内核模型。除在英特尔平台上展示自身基准测试结果外，我们还综合了近期关于多种SYCL实现及编译器的研究成果。我们的结果揭示了当前SYCL实现中的关键局限性与不一致性，并为提升该框架的可靠性及跨平台可用性提供了所需步骤的见解。