FP64 Ray-Trace
This benchmark measures the double precision (also known as 64-bit) floating-point performance through the computation of a scene with a SIMD-enhanced ray tracing engine. The code behind this benchmark method is written in Assembly, and it is extremely optimized for every popular AMD, Intel and VIA processor core variants by utilizing the appropriate x87, SSE, SSE2, SSE3, SSSE3, SSE4.1, AVX, AVX2, FMA, and FMA4 instruction set extension.
FP64 Ray-Trace test is HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
Мини ПК Topton Mini PC на базе AMD Ryzen 5000U серии
Когда пришла пора поменять свой старый ноутбук на что-то посовременнее, я, сделав несколько подходов, остановился на этом китайском мини ПК. Одним из основных критериев, помимо цены, было наличие видеокарты, которая могла бы чуть больше, чем просто выводить картинку на монитор, поэтому варианты на базе процессоров Intel я отмёл после изучения нескольких сравнительных обзоров с процессорами AMD Ryzen.
Планируя сэкономить, я выбирал вариант barebone: без ОЗУ, жёсткого диска/SSD, WiFi. SSD NVMe у меня был свой, память купил со скидкой в одном из российских онлайн магазинов, диск HDD 2.5″ также у меня был свой, WiFi модуль с поддержкой 802.11ax заказал на китайской площадке.
В итоге свой выбор я остановил на Topton Mini PC (номера модели не предусмотрено, ориентироваться остаётся по фото и характеристикам) на базе процессора AMD Ryzen 3 5400U. Фотографии частично взял со страницы производителя, т.к. лучше я сфотографировать не смогу.
Topton Mini PC на базе AMD Ryzen 5000U серии
По самому производителю Topton у меня сложилось двоякое впечатление: вроде бы они и являются производителем (или только заказчиком?) с широким ассортиментом мини ПК с интересными характеристиками, но все их сайты ориентированы на продажи и никакой поддержки (драйверов, инструкций, BIOS) не предусмотрено, остаётся только писать им письма или обращения в чат.
Подгадав покупку на период распродаж 11.11, я сделал заказ выбранного мини ПК на известной китайской площадке, применив всевозможные купоны и скидку продавца. Сумма получилась чуть более 25 000 р., что очень даже неплохо в сравнении с тем, что можно купить у нас за эти деньги. Доставка курьером в РФ — чуть более месяца. Что приятно — не пришлось платить пошлину, т.к. продавец указал, что это корпус для ПК со стоимостью $100.
Мини ПК упакован в большую картонную коробку небесного цвета, в комплекте идёт блок питания, HDMI кабель, SATA кабель с питанием, краткая инструкция, набор винтов для крепления диска, планка для крепления к монитору сзади (VESA 75х75, 100×100). Несмотря на то, что WiFi модуль я не заказывал, на крышке мини ПК были выведены провода антенн.
«Живое» фото свежераспакованного мини ПК
Как видно на фото, крышка верхняя глянцевая пластиковая (приклеена на металлическое основание) с защитной плёнкой. Фиксируется на корпусе двумя винтами с одной стороны, с другой — выступы на крышке вставляются в пазы внутри корпуса.
Итак, характеристики купленной модификации:
Характеристика
Значение
AMD Ryzen 5400U (архитектура Zen 3, 4 ядра, 8 потоков, 2.6 — 4 ГГц, TDP 15-20 Вт *)
Benchmarking
Benchmark pages of AIDA64 Extreme provide several methods to measure system performance. These benchmarks are synthetic, so their results show only the theoretical (maximum) performance of the system.
CPU and FPU benchmarks of AIDA64 Extreme are built on the multi-threaded AIDA64 Benchmark Engine that supports up to 1280 simultaneous processing threads. It also supports multi-processor, multi-core and HyperThreading enabled systems.
Ray tracing benchmarks
These benchmarks measure the single and double precision (also known as 32-bit and 64-bit) floating-point performance through the computation of a scene with a SIMD-enhanced ray tracing engine. The code behind this benchmark method is written in Assembly, and it is extremely optimized for every popular AMD, Intel and VIA processor core variants by utilizing the appropriate x87, SSE, SSE2, SSE3, SSSE3, SSE4.1, AVX, AVX2, XOP, FMA, FMA4 and AVX-512 instruction set extension. Both FP32 and FP64 Ray-Trace test is HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
Memory Tests
Memory bandwidth benchmarks (Memory Read, Memory Write, Memory Copy) measure the maximum achievable memory data transfer bandwidth. The code behind these benchmark methods are written in Assembly and they are extremely optimized for every popular AMD, Intel and VIA processor achieveablecore variants by utilizing the appropriate x86/x64, x87, MMX, MMX+, 3DNow!, SSE, SSE2, SSE4.1, AVX, AVX2 and AVX-512 instruction set extension.
The Memory Latency benchmark measures the typical delay when the CPU reads data from system memory. Memory latency time means the penalty measured from the issuing of the read command until the data arrives to the integer registers of the CPU.
CPU Queen Benchmark
This simple integer benchmark focuses on the branch prediction capabilities and the misprediction penalties of the CPU. It finds the solutions for the classic «Queens problem» on a 10 by 10 sized chessboard. At the same clock speed theoretically the processor with the shorter pipeline and smaller misprediction penalties will attain higher benchmark scores. For example — with HyperThreading disabled — the Intel Northwood core processors get higher scores than the Intel Prescott core based ones due to the 20-step vs 31-step long pipeline. CPU Queen test uses integer MMX, SSE2 and SSSE3 optimizations.
CPU PhotoWorxx Benchmark
This benchmark performs different common tasks used during digital photo processing.
It performs the following tasks on a very large RGB image:
- Fill the image with random colored pixels
- Rotate 90 degrees CCW
- Rotate 180 degrees
- Difference
- Color space conversion (used e.g. during JPEG conversion)
This benchmark stresses the SIMD integer arithmetic execution units of the CPU and also the memory subsystem. CPU PhotoWorxx test uses the appropriate x87, MMX, MMX+, 3DNow!, 3DNow!+, SSE, SSE2, SSSE3, SSE4.1, SSE4A, AVX, AVX2, XOP and AVX-512 instruction set extension and it is NUMA, HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
CPU ZLib Benchmark
This integer benchmark measures combined CPU and memory subsystem performance through the public ZLib compression library. CPU ZLib test uses only the basic x86 instructions, and it is HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
CPU AES Benchmark
This benchmark measures CPU performance using AES (Advanced Encryption Standard) data encryption. In cryptography AES is a symmetric-key encryption standard. AES is used in several compression tools today, like 7z, RAR, WinZip, and also in disk encryption solutions like BitLocker, FileVault (Mac OS X), TrueCrypt.
CPU AES test uses the appropriate x86, MMX and SSE4.1 instructions, and it’s hardware accelerated on VIA PadLock Security Engine capable VIA C3, VIA C7, VIA Nano and VIA QuadCore processors; and on Intel AES-NI instruction set extension and the future VAES capable processors. The test is HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
CPU Hash Benchmark
This benchmark measures CPU performance using the SHA1 hashing algorithm defined in the Federal Information Processing Standards Publication 180-4. The code behind this benchmark method is written in Assembly, and it is optimized for every popular AMD, Intel and VIA processor core variants by utilizing the appropriate MMX, MMX+/SSE, SSE2, SSSE3, AVX, AVX2, XOP, BMI, BMI2 and AVX-512 instruction set extension. CPU Hash benchmark is hardware accelerated on VIA PadLock Security Engine capable VIA C7, VIA Nano and VIA QuadCore processors.
FPU Julia Benchmark
This benchmark measures the single precision (also known as 32-bit) floating-point performance through the computation of several frames of the popular «Julia» fractal. The code behind this benchmark method is written in Assembly, and it is extremely optimized for every popular AMD, Intel and VIA processor core variants by utilizing the appropriate x87, 3DNow!, 3DNow!+, SSE, AVX, AVX2, FMA, FMA4 and AVX-512 instruction set extension. FPU Julia test is HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
FPU Mandel Benchmark
This benchmark measures the double precision (also known as 64-bit) floating-point performance through the computation of several frames of the popular «Mandelbrot» fractal. The code behind this benchmark method is written in Assembly, and it is extremely optimized for every popular AMD, Intel and VIA processor core variants by utilizing the appropriate x87, SSE2, AVX, AVX2, FMA, FMA4 and AVX-512 instruction set extension. FPU Mandel test is HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
FPU SinJulia Benchmark
This benchmark measures the extended precision (also known as 80-bit) floating-point performance through the computation of a single frame of a modified «Julia» fractal. The code behind this benchmark method is written in Assembly, and it is extremely optimized for every popular AMD, Intel and VIA processor core variants by utilizing trigonometric and exponential x87 instructions. FPU SinJulia is HyperThreading, multi-processor (SMP) and multi-core (CMP) aware.
Benchmark
AIDA64 offers dedicated microbenchmarks, which are available under the Benchmark category in the Page menu. These are synthetic benchmarks, which means that they can be used to measure the theoretical maximum performance of the system. Memory bandwidth, CPU and FPU benchmarks are built on the multi-threaded AIDA64 benchmark engine that – since AIDA64 Business v4.00 – supports up to 640 simultaneous processing threads and 10 processor groups.
Thanks to AIDA64’s huge reference result database, benchmark results can be compared to those of other configurations. By clicking the “Results” button on the toolbar, we can save and manage our benchmark results, and we can also hide reference results and user results, which are listed on the results page by default.
Memory read, write, copy and latency
Memory benchmarks measure the maximum bandwidth achievable when performing the selected operations (read, write, copy). The memory latency benchmark measures the time it takes for data to arrive in the integer registers of the CPU after the issue of the read command.
CPU Queen
This simple integer benchmark focuses on the CPU’s branch prediction capabilities and branch misprediction penalties. It calculates solutions for the classic “N queens puzzle” on a 10×10 chessboard.
CPU PhotoWorxx
This integer benchmark measure CPU performance with several 2D photo processing algorithms. The test mainly stresses the SIMD integer arithmetic execution units of the CPU and the memory subsystem.
CPU ZLib
This integer benchmark measures combined CPU and memory subsystem performance using the public ZLib compression library.
CPU AES
This integer benchmark measures CPU performance using AES (Advanced Encryption Standard) data encryption.
CPU Hash
This integer benchmark measures CPU performance using the SHA1 hashing algorithm.
FPU VP8
This benchmark measures video compression performance using version 1.1.0 of the Google VP8 (WebM) video codec.
FPU Julia
This benchmark measures the single precision (or 32-bit) floating-point performance through the computation of several “Julia” fractal frames.
FPU Mandel
This benchmark measures the double precision (or 64-bit) floating-point performance through the computation of several “Mandelbrot” fractal frames.
FPU SinJulia
This benchmark measures the extended precision (or 80-bit) floating-point performance through the computation of a single frame of a modified “Julia” fractal.
FP32 Ray-Trace
This benchmark measures the single precision (also known as 32-bit) floating-point performance through the computation of a scene with a SIMD-enhanced ray tracing engine.
FP64 Ray-Trace
This benchmark measures the double precision (also known as 64-bit) floating-point performance through the computation of a scene with a SIMD-enhanced ray tracing engine.